Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Li, Mengmeng | Zhang, Chiping | Chen, Minghao | Xu, Weihua

Article Type: Research Article

Abstract: Multi-granulation decision-theoretic rough sets uses the granular structures induced by multiple binary relations to approximate the target concept, which can get a more accurate description of the approximate space. However, Multi-granulation decision-theoretic rough sets is very time-consuming to calculate the approximate value of the target set. Local rough sets not only inherits the advantages of classical rough set in dealing with imprecise, fuzzy and uncertain data, but also breaks through the limitation that classical rough set needs a lot of labeled data. In this paper, in order to make full use of the advantage of computational efficiency of local rough …sets and the ability of more accurate approximation space description of multi-granulation decision-theoretic rough sets, we propose to combine the local rough sets and the multigranulation decision-theoretic rough sets in the covering approximation space to obtain the local multigranulation covering decision-theoretic rough sets model. This provides an effective tool for discovering knowledge and making decisions in relation to large data sets. We first propose four types of local multigranulation covering decision-theoretic rough sets models in covering approximation space, where a target concept is approximated by employing the maximal or minimal descriptors of objects. Moreover, some important properties and decision rules are studied. Meanwhile, we explore the reduction among the four types of models. Furthermore, we discuss the relationships of the proposed models and other representative models. Finally, illustrative case of medical diagnosis is given to explain and evaluate the advantage of local multigranulation covering decision-theoretic rough sets model. Show more

Keywords: Covering rough sets, local rough sets, local covering rough sets, multigranulation rough sets

DOI: 10.3233/JIFS-202274

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2021

Authors: Liu, Xiaowei

Article Type: Research Article

Abstract: How to measure the level of intellectual property protection has been the focus of academic and practical circles, however, rigorous empirical evidence remains scant. The influencing factors of intellectual property protection are summarized and analyzed, and the evaluation index system of intellectual property protection at the provincial level is constructed with judicial, administrative, pluralistic, and environmental protections as the first-class indicators. The feasibility and reliability of the index system are tested empirically by using the 2019 data of intellectual property protection in certain provinces and cities in China. The index system can objectively reflect the level of intellectual property protection …in provincial regions. The research has certain enlightenment to strengthen the performance appraisal of intellectual property protection and improve the level of intellectual property protection in the region and even in the country. Show more

Keywords: Intellectual property protection, fuzzy comprehensive evaluation, index system

DOI: 10.3233/JIFS-189910

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Zhaohua, Leng

Article Type: Research Article

Abstract: With the prevalence of international trade protectionism and transformation and upgrading of domestic market structure, the contradiction between demand and competitive development port market of the Yangtze River Delta in China has become increasingly prominent. Nineteen major ports of Yangtze River Delta in China were selected, using the methods of factor analysis, fuzzy clustering, gravitational model, the spatial effects in the hinterland were calculated from three dimensions: central potential, spatial gravity and distribution convenience, and the regional coordination of port services was analyzed. The results show that the potential of Shanghai Port and Ningbo-Zhoushan Port in China is stronger, and …the distribution difference is quite obvious. The spatial gravity of each port city superimposes to form an obvious dense semi-circular zone, and the participation ability of the marginal ports is weak. The distribution convenience in hinterland changes from location-dependent to traffic-dependent. The service gap in the hinterland of the port system is more significant, but the expansions of spatial effects make regional coordination gradually improve. Show more

Keywords: Yangtze River Delta, port service, spatial effect, regional coordination

DOI: 10.3233/JIFS-189919

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Nawar, Ashraf S. | Atef, Mohammed | Khalil, Ahmed Mostafa

Article Type: Research Article

Abstract: The aim of this paper is to introduce and study different kinds of fuzzy soft β -neighborhoods called fuzzy soft β -adhesion neighborhoods and to analyze some of their properties. Further, the concepts of soft β -adhesion neighborhoods are investigated and the related properties are studied. Then, we present new kinds of lower and upper approximations by means of different fuzzy soft β -neighborhoods. The relationships among our models (i.e., Definitions 3.9, 3.12, 3.15 and 3.18) and Zhang models [48 ] are also discussed. Finally, we construct an algorithm based on Definition 3.12, when k  = 1 to solve the decision-making …problems and illustrate its applicability through a numerical example. Show more

Keywords: Fuzzy soft β-covering, Fuzzy soft β-neighborhoods, Fuzzy soft β-adhesion neighborhoods, Decision-making

DOI: 10.3233/JIFS-201822

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Li, Peng | Wei, Cuiping

Article Type: Research Article

Abstract: With the sharp increase in the elderly population and the gradual invalidation of traditional long-term care style, the supply-demand contradiction for nursing homes services appears. A suitable evaluation mechanism is very useful to resolve the contradiction. The evaluation process can be seen as a multiple criteria decision making (MCDM) problem. Because some criteria are subjective and the evaluation process usually needs more than one decision maker (DM), probabilistic linguistic information is suitable to express DMs’ opinions. Therefore, we propose a novel EDAS method with probabilistic linguistic information based on D-S evidence theory for evaluating nursing homes. First, a new score …function for probabilistic linguistic term set (PLTS) is put forward in order to compare PLTSs and use EDAS method conveniently. Then, a novel uncertainty measure based on D-S evidence theory is proposed to obtain the criteria weights. Furthermore, a novel EDAS method for PLTSs based on cobweb area model is put forward to reduce the effect of some extreme values influencing the decision result. Finally, our method is applied to a real case of evaluating nursing homes in Nanjing city, and the effectiveness of our method is illustrated by comparing the traditional decision methods. Show more

Keywords: Evaluation, nursing home, probabilistic linguistic term set, D-S evidence theory

DOI: 10.3233/JIFS-201866

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Tao, Tian | Tiantian, Zhang | Xiaoning, Li | Dajian, Tong

Article Type: Research Article

Abstract: A TOPSIS evaluation index system of entropy weight of enterprise internal control quality based on fuzzy matter-element model was established to master the enterprise internal control quality comprehensively and analyze its influences on enterprise innovation performance accurately. Firstly, a composite fuzzy matter-element model was established based on the fuzzy matter-element theory. Secondly, weights of evaluation indexes were determined by the entropy weight method. Thirdly, the concept of relative closeness was developed by comparison with positive and negative ideal indexes. Finally, the internal control quality levels of 781 listed companies in Chin were measured by TOPSIS method. Results show that: weights …of five level-1 indexes for enterprise internal control quality evaluation are different. Specifically, weights of Law & Regulation, Operation and Strategy are higher than those of Financial Statements and Assets Safety. In the level-2 index system, weights of “major litigation and arbitration cases”, “turnover of total assets” and “Tobin’s Q” occupy 66% of total weights. Listed companies which occupy the top10 position in term of internal control quality mainly belong to industries requiring strict monitoring and control over safety production. Enterprise internal control quality differs significantly among different industries. Research conclusions can provide methods and practical references to evaluate internal control quality of Chinese enterprises. Show more

Keywords: Fuzzy matter-element model, entropy weight TOPSIS evaluation, enterprise internal control quality, evaluation indexes

DOI: 10.3233/JIFS-189901

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2021

Authors: Jing, Xu | Yixuan, Lu | Panqian, Dai | Kaixin, Yu | Kun, Chen

Article Type: Research Article

Abstract: This manuscript aims to explore the impact of production organization mode on the inventory and delivery rate of pump enterprises and optimize the production management of pump enterprises. The system dynamic model and simulation test method were used to compare the changes in the inventory, productivity and delivery rate of pump enterprise under the traditional make-to-order (MTO) and make-to-stock (MTS) organizational modes. Following the above analysis, the optimized pump order production management mode combined with MTO & MTS was put forward, and the fuzzy comprehensive evaluation method was used to evaluate the three above modes. When customer demand scarcely fluctuates …and is easily predictable, the MTO production organization mode can be adopted; when customer demand fluctuates sharply and is difficultly predicted, the MTO & MTS combined mode should be selected. According to the results of the fuzzy comprehensive evaluation, the MTO & MTS mode is the best choice for pump enterprises. Considering that the pump demand is sensitive to the season and natural environment, the optimized mode is suitable for the production and inventory management of pump enterprise. Show more

Keywords: Make to order, make to stock, pump, production management

DOI: 10.3233/JIFS-189906

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2021

Authors: Wang, Degang | Li, Dongling | Sun, Li | Zhang, Zhenke | Cheng, Jie | Yu, Miao

Article Type: Research Article

Abstract: There are 11 provinces along the coastal regions in the Chinese Mainland and the scientific division of marine management boundaries among different provinces within the extents of the territorial sea is of important significance in promoting the sustainable development of the marine economy in China. A fuzzy evaluation index system that includes 14 indices of three subsets was established based on a case study of maritime boundary delimitation between Jiangsu and Shandong Provinces to evaluate the advantages and disadvantages of maritime boundary delimitation and determine the optimal scheme and offset shortages in the current evaluation index system and evaluation methods. …Combined weights of indices were calculated through the analytic hierarchy process (AHP) and entropy weight method. The comprehensive evaluation indices were used to evaluate three maritime boundary delimitation schemes, namely, historical boundary delimitation scheme, angle bisector delimitation scheme, and equidistance delimitation scheme. Results show that the equidistance delimitation scheme is relatively superior to the two other schemes. The evaluation index is 0.504761 and the evaluation grade is “good”. The angle bisector delimitation scheme is the second optimal. The evaluation index is 0.361641 and the grade is “moderate”. The historical boundary delimitation scheme is the poorest. The evaluation index is 0.135345 and the grade is “poor”. In the late optimization of maritime boundary delimitation schemes, more consideration should be given to people’s livelihood and protection of national maritime rights and interests. The fuzzy comprehensive evaluation method based on AHP-entropy weight can not only provide a quantitative top-down sequence of schemes in terms of quality and solve estimation problems in maritime boundary delimitation scheme, but also assist decision-makers to select the best scheme. Therefore, it possesses great application values. Show more

Keywords: Maritime boundary delimitation, delimitation scheme, AHP-entropy weight method, fuzzy evaluation method

DOI: 10.3233/JIFS-189904

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Jing, Hongjun | Yao, Ping | Song, Lichen | Zhang, Jiahao | Zhao, Yanlong | Zhang, Zhong

Article Type: Research Article

Abstract: With modern economic and social development, the technical and economic requirements of highway maintenance and construction projects have become increasingly complicated. Meticulous and in-depth investigation and demonstration guided by scientific theories and methods are of considerable importance to highway maintenance scheme decision. As basis for the selection of highway asphalt pavement recycling maintenance scheme, the factors influencing the decision are analytically demonstrated and an evaluation system is proposed, including three major decision indexes: applicability of recycling mode, recycled pavement quality recovery index, and economic benefit. According to the principles of data statistics and analysis, this study proposes a calculation method …for the recycled pavement quality recovery index, analyzes the economic benefits of decision schemes using economic models such as recycling ratio and cost, and puts forward an optimal evaluation method of engineering cost and its fuzzy score intervals. Index weights are calculated through the analytic hierarchy process, and the comprehensive decision evaluation system and comprehensive evaluation method are established. Subsequently, the decision-making method is analyzed on the basis of the decision system by combining the related data. Results show maximum weight of the pavement quality recovery index and minor differences among four recycling schemes in the quality recovery index and applicability. The decision-making results are simplified with clear hierarchical feature because of the fuzzy score intervals of each index. Findings can provide a reference for the asphalt pavement recycling scheme decision. Show more

Keywords: Road engineering, recycling maintenance, intelligent decision-making, fuzzy evaluation

DOI: 10.3233/JIFS-189900

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Preethi, D. | Vimala, J.

Article Type: Research Article

Abstract: This paper introduces the concept of homomorphism on fuzzy hyperlattice ordered group ( FHLOG ) . It studies how the binary and the fuzzy hyperoperations of a FHLOG can be transformed into the binary and the fuzzy hyperoperations of another FHLOG . The notion of fuzzy hypercongruence relation on FHLOG is also defined. The paper also establishes the redox reaction of copper, gold and americium forms three FHLOG s. Besides, homomorphism and composition function of FHLOG …s using the redox reactions are developed. Therefore, the paper develops a relation among three different metal’s redox reactions in which the binary and the fuzzy hyperoperations, are preserved. Show more

Keywords: Lattice ordered group, fuzzy lattice ordered group, fuzzy hyperlattice, fuzzy hyperlattice ordered group, homomorphism, redox reactions

DOI: 10.3233/JIFS-189888

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Vasudevan, Nisha | Venkatraman, Vasudevan | Ramkumar, A | Sheela, A

Article Type: Research Article

Abstract: Smart grid is a sophisticated and smart electrical power transmission and distribution network, and it uses advanced information, interaction and control technologies to build up the economy, effectiveness, efficiency and grid security. The accuracy of day-to-day power consumption forecasting models has an important impact on several decisions making, such as fuel purchase scheduling, system security assessment, economic capacity generation scheduling and energy transaction planning. The techniques used for improving the load forecasting accuracy differ in the mathematical formulation as well as the features used in each formulation. Power utilization of the housing sector is an essential component of the overall …electricity demand. An accurate forecast of energy consumption in the housing sector is quite relevant in this context. The recent adoption of smart meters makes it easier to access electricity readings at very precise resolutions; this source of available data can, therefore, be used to build predictive models., In this study, the authors have proposed Prophet Forecasting Model (PFM) for the application of forecasting day-ahead power consumption in association with the real-time power consumption time series dataset of a single house connected with smart grid near Paris, France. PFM is a special type of Generalized Additive Model. In this method, the time series power consumption dataset has three components, such as Trend, Seasonal and Holidays. Trend component was modelled by a saturating growth model and a piecewise linear model. Multi seasonal periods and Holidays were modelled with Fourier series. The Power consumption forecasting was done with Autoregressive Integrated Moving Average (ARIMA), Long Short Term Neural Memory Network (LSTM) and PFM. As per the comparison, the improved RMSE, MSE, MAE and RMSLE values of PFM were 0.2395, 0.0574, 0.1848 and 0.2395 respectively. From the comparison results of this study, the proposed method claims that the PFM is better than the other two models in prediction, and the LSTM is in the next position with less error. Show more

Keywords: Energy management, smart home, energy forecast, power management, efficiency

DOI: 10.3233/JIFS-189886

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Krishnamoorthy, Amrutha | Sindhura, Vijayasimha Reddy | Gowtham, Devarakonda | Jyotsna, C. | Amudha, J.

Article Type: Research Article

Abstract: Extraction of eye gaze events is highly dependent on automated powerful software that charges exorbitant prices. The proposed open-source intelligent tool StimulEye helps to detect and classify eye gaze events and analyse various metrics related to these events. The algorithms for eye event detection in use today heavily depend on hand-crafted signal features and thresholding, which are computed from the stream of raw gaze data. These algorithms leave most of their parametric decisions on the end user which might result in ambiguity and inaccuracy. StimulEye uses deep learning techniques to automate eye gaze event detection which neither requires manual decision …making nor parametric definitions. StimulEye provides an end to end solution which takes raw streams of data from an eye tracker in text form, analyses these to classify the inputs into the events, namely saccades, fixations, and blinks. It provides the user with insights such as scanpath, fixation duration, radii, etc. Show more

Keywords: Eye tracking, fixations, saccades, scanpath, deep learning

DOI: 10.3233/JIFS-189893

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Sujatha, M. | Geetha, K. | Balakrishnan, P.

Article Type: Research Article

Abstract: The widespread adoption of cloud computing by several companies across diverse verticals of different sizes has led to an exponential growth of Cloud Service Providers (CSP). Multiple CSPs offer homogeneous services with a vast array of options and different pricing policies, making the suitable service selection process complex. Our proposed model simplifies the IaaS selection process that can be used by all users including clients from the non-IT background. In the first phase, requirements are gathered using a simple questionnaire and are mapped with the compute services among different alternatives.In the second phase, we have implemented the Sugeno Fuzzy inference …system to rank the service providers based on the QoS attributes to ascertain the appropriate selection. In the third phase, we have applied the cost model to identify the optimal CSP. This framework is validated by applying it for a gaming application use case and it has outperformed the online tools thus making it an exemplary model. Show more

Keywords: Cloud computing, IaaS selection, Sugeno Fuzzy inference system, CSP selection, compute service, MCDM

DOI: 10.3233/JIFS-189883

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Jeyanthi, R. | Sahithi, Madugula | Sireesha, N.V.L. | Srinivasan, Mangala Sneha | Devanathan, Sriram

Article Type: Research Article

Abstract: In process industries, measurements usually contain errors due to the improper instrumental variation, physical leakages in process streams and nodes, and inaccurate recording/reporting. Thus, these measurements violate the laws of conservation, and do not conform to process constraints. Data reconciliation (DR) is used to resolve the difference between measurements and constraints. DR is also used in reducing the effect of random errors and more accurately estimating the true values. A multivariate technique that is used to obtain estimates of true values while preserving the most significant inherent variation is Principal Component Analysis (PCA). PCA is used to reduce the dimensionality …of the data with minimum information loss. In this paper, two new DR techniques are proposed moving-average PCA (MA-PCA) and exponentially weighted moving average PCA (EWMA-PCA) to improve the performance of DR and obtain more accurate and consistent data. These DR techniques are compared based on RMSE. Further, these techniques are analyzed for different values of sample size, weighting factor, and variances. Show more

Keywords: Data reconciliation, MA-PCA, EWMA-PCA

DOI: 10.3233/JIFS-189892

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2021

Authors: Shabir, Muhammad | Mubarak, Asad | Naz, Munazza

Article Type: Research Article

Abstract: The rough set theory is an effective method for analyzing data vagueness, while bipolar soft sets can handle data ambiguity and bipolarity in many cases. In this article, we apply Pawlak’s concept of rough sets to the bipolar soft sets and introduce the rough bipolar soft sets by defining a rough approximation of a bipolar soft set in a generalized soft approximation space. We study their structural properties and discuss how the soft binary relation affects the rough approximations of a bipolar soft set. Two sorts of bipolar soft topologies induced by soft binary relation are examined. We additionally discuss …some similarity relations between the bipolar soft sets, depending on their roughness. Such bipolar soft sets are very useful in the problems related to decision-making such as supplier selection problem, purchase problem, portfolio selection, site selection problem etc. A methodology has been introduced for this purpose and two algorithms are presented based upon the ongoing notions of foresets and aftersets respectively. These algorithms determine the best/worst choices by considering rough approximations over two universes i.e. the universe of objects and universe of parameters under a single framework of rough bipolar soft sets. Show more

Keywords: Rough sets, bipolar soft sets, rough bipolar soft sets, bipolar soft topology, decision making

DOI: 10.3233/JIFS-202958

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-1, 2021

Authors: Adu, Kwabena | Yu, Yongbin | Cai, Jingye | Dela Tattrah, Victor | Adu Ansere, James | Tashi, Nyima

Article Type: Research Article

Abstract: The squash function in capsule networks (CapsNets) dynamic routing is less capable of performing discrimination of non-informative capsules which leads to abnormal activation value distribution of capsules. In this paper, we propose vertical squash (VSquash) to improve the original squash by preventing the activation values of capsules in the primary capsule layer to shrink non-informative capsules, promote discriminative capsules and avoid high information sensitivity. Furthermore, a new neural network, (i) skip-connected convolutional capsule (S-CCCapsule), (ii) Integrated skip-connected convolutional capsules (ISCC) and (iii) Ensemble skip-connected convolutional capsules (ESCC) based on CapsNets are presented where the VSquash is applied in the dynamic …routing. In order to achieve uniform distribution of coupling coefficient of probabilities between capsules, we use the Sigmoid function rather than Softmax function. Experiments on Guangzhou Women and Children’s Medical Center (GWCMC), Radiological Society of North America (RSNA) and Mendeley CXR Pneumonia datasets were performed to validate the effectiveness of our proposed methods. We found that our proposed methods produce better accuracy compared to other methods based on model evaluation metrics such as confusion matrix, sensitivity, specificity and Area under the curve (AUC). Our method for pneumonia detection performs better than practicing radiologists. It minimizes human error and reduces diagnosis time. Show more

Keywords: Artificial intelligence, capsule network, convolutional neural network, deep learning, pneumonia, x-ray imaging

DOI: 10.3233/JIFS-202638

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-25, 2021

Authors: Recal, Füsun | Demirel, Tufan

Article Type: Research Article

Abstract: Although Machine Learning (ML) is widely used to examine hidden patterns in complex databases and learn from them to predict future events in many fields, utilization of it for predicting the outcome of occupational accidents is relatively sparse. This study utilized diversified ML algorithms; Multinomial Logistic Regression (MLR), Support Vector Machines (SVM), Single C5.0 Tree (C5), Stochastic Gradient Boosting (SGB), and Neural Network (NN) in classifying the severity of occupational accidents in binary (Fatal/NonFatal) and multi-class (Fatal/Major/Minor) outcomes. Comparison of the performance of models showed Balanced Accuracy to be the best for SVM and SGB methods in 2-Class and SGB …in 3-Class. Algorithms performed better at predicting fatal accidents compared to major and minor accidents. Results obtained revealed that, ML unveils factors contributing to severity to better address the corrective actions. Furthermore, taking action related to even some of the most significant factors in complex accidents database with many attributes can prevent majority of severe accidents. Interpretation of most significant factors identified for accident prediction suggest the following corrective measures: taking fall prevention actions, prioritizing workplace inspections based on the number of employees, and supplementing safety actions according to worker’s age and experience. Show more

Keywords: Accidents severity, classification, data mining, feature selection; machine learning

DOI: 10.3233/JIFS-202099

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2021

Authors: Wang, Shuang | Ding, Lei | Sui, He | Gu, Zhaojun

Article Type: Research Article

Abstract: Cybersecurity risk assessment is an important means of effective response to network attacks on industrial control systems. However, cybersecurity risk assessment process is susceptible to subjective and objective effects. To solve this problem, this paper introduced cybersecurity risk assessment method based on fuzzy theory of Attack-Defense Tree model and probability cybersecurity risk assessment technology, and applied it to airport automatic fuel supply control system. Firstly, an Attack-Defense Tree model was established based on the potential cybersecurity threat of the system and deployed security equipment. Secondly, the interval probability of the attack path was calculated using the triangular fuzzy quantification of …the interval probabilities of the attack leaf nodes and defensive leaf nodes. Next, the interval probability of the final path was defuzzified. Finally, the occurrence probability of each final attack path was obtained and a reference for the deployment of security equipment was provided. The main contributions of this paper are as follows: (1) considering the distribution of equipment in industrial control system, a new cybersecurity risk evaluation model of industrial control system is proposed. (2) The experimental results of this article are compared with other assessment technologies, and the trend is similar to that of other evaluation methods, which proves that the method was introduced in this paper is scientific. However, this method reduces the subjective impact of experts on cybersecurity risk assessment, and the assessment results are more objective and reasonable. (3) Applying this model to the airport oil supply automatic control system can comprehensively evaluate risk, solve the practical problems faced by the airport, and also provide an important basis for the cybersecurity protection scheme of the energy industry. Show more

Keywords: Cybersecurity risk assessment, fuzzy set theory, attack-defense tree

DOI: 10.3233/JIFS-201126

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2021

Authors: An, Qing | Tang, Ruoli | Su, Hongfeng | Zhang, Jun | Li, Xin

Article Type: Research Article

Abstract: Due to the promising performance on energy-saving, the building integrated photovoltaic system (BIPV) has found an increasingly wide utilization in modern cities. For a large-scale PV array installed on the facades of a super high-rise building, the environmental conditions (e.g., the irradiance, temperature, sunlight angle etc.) are always complex and dynamic. As a result, the PV configuration and maximum power point tracking (MPPT) methodology are of great importance for both the operational safety and efficiency. In this study, some famous PV configurations are comprehensively tested under complex shading conditions in BIPV application, and a robust configuration for large-scale BIPV system …based on the total-cross-tied (TCT) circuit connection is developed. Then, by analyzing and extracting the feature variables of environment parameters, a novel fast MPPT methodology based on extreme learning machine (ELM) is proposed. Finally, the proposed configuration and its MPPT methodology are verified by simulation experiments. Experimental results show that the proposed configuration performs efficient on most of the complex shading conditions, and the ELM-based intelligent MPPT methodology can also obtain promising performance on response speed and tracking accuracy. Show more

Keywords: Building integrated photovoltaic system, maximum power point tracking, PV configuration, intelligent control, extreme learning machine

DOI: 10.3233/JIFS-210424

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2021

Authors: Rajavel, Rajkumar | Ravichandran, Sathish Kumar | Nagappan, Partheeban | Ramasubramanian Gobichettipalayam, Kanagachidambaresan

Article Type: Research Article

Abstract: A major demanding issue is developing a Service Level Agreement (SLA) based negotiation framework in the cloud. To provide personalized service access to consumers, a novel Automated Dynamic SLA Negotiation Framework (ADSLANF) is proposed using a dynamic SLA concept to negotiate on service terms and conditions. The existing frameworks exploit a direct negotiation mechanism where the provider and consumer can directly talk to each other, which may not be applicable in the future due to increasing demand on broker-based models. The proposed ADSLANF will take very less total negotiation time due to complicated negotiation mechanisms using a third-party broker agent. …Also, a novel game theory decision system will suggest an optimal solution to the negotiating agent at the time of generating a proposal or counter proposal. This optimal suggestion will make the negotiating party aware of the optimal acceptance range of the proposal and avoid the negotiation break off by quickly reaching an agreement. Show more

Keywords: Service level agreement, broker-based negotiation framework, game theory decision system, E-commerce application

DOI: 10.3233/JIFS-189882

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Pradhan, Rosy | Khan, Mohammad Rafique | Sethy, Prabir Kumar | Majhi, Santosh Kumar

Article Type: Research Article

Abstract: The field of optimization science is proliferating that has made complex real-world problems easy to solve. Metaheuristics based algorithms inspired by nature or physical phenomena based methods have made its way in providing near-ideal (optimal) solutions to several complex real-world problems. Ant lion Optimization (ALO) has inspired by the hunting behavior of antlions for searching for food. Even with a unique idea, it has some limitations like a slower rate of convergence and sometimes confines itself into local solutions (optima). Therefore, to enhance its performance of classical ALO, quantum information theory is hybridized with classical ALO and named as QALO …or quantum theory based ALO. It can escape from the limitations of basic ALO and also produces stability between processes of explorations followed by exploitation. CEC2017 benchmark set is adopted to estimate the performance of QALO compared with state-of-the-art algorithms. Experimental and statistical results demonstrate that the proposed method is superior to the original ALO. The proposed QALO extends further to solve the model order reduction (MOR) problem. The QALO based MOR method performs preferably better than other compared techniques. The results from the simulation study illustrate that the proposed method effectively utilized for global optimization and model order reduction. Show more

Keywords: Antlion optimization, quantum information theory, model order reduction, metahueristic optimization, CEC benchmark

DOI: 10.3233/JIFS-189894

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Lili, Xu | Feng, Liu | Xuejian, Chu

Article Type: Research Article

Abstract: This study examines the application of the business model of supply chain finance depending on the core enterprise, to the credit financing of transportation capacity enterprises. It studies the credit transmission characteristics regarding core enterprise credit radiation, presents the core enterprise credit segmentation and credit pricing, and transforms them into the calculation of credit guarantee and the default probability of core enterprises. Credit guarantee is regarded as a constraint of financial institutions’ credit decisions. Using probability density and logistic tools, we construct a profit maximization model for financial institutions and solve their optimal credit decision for a specific interest rate. …Through numerical experiments, we verify the validity of the model and conclude that increasing the business volume between financing enterprises and core enterprises or reducing the probability of default can effectively improve financial institutions’ credit line. Show more

Keywords: Credit segmentation, credit pricing, default probability, transportation capacity financing, credit decision

DOI: 10.3233/JIFS-201818

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2021

Authors: Özgül, Ercan | Dinçer, Hasan | Yüksel, Serhat

Article Type: Research Article

Abstract: Healthy life is recognized as one of the most fundamental human rights. However, even today, millions of people around the world are forced to choose between their basic needs and fundamental rights. Half of the world’s population does not have access to the healthcare they need. Universal Health Coverage (UHC) aims to ensure that all individuals receive the quality health services they need without incurring a financial burden, and to protect them from risk factors that threaten their health. The aim of this study is to identify the significant factors to improve UHC in the countries. For this purpose, house …of quality (HoQ) approach is used in the analysis process so that both customer expectations and technical requirements are considered. Within this framework, a novel hybrid model has been proposed which has three different stages. Firstly, 3 groups of diseases and 4 clinical services for each group are determined regarding the customer needs. Secondly, these factors are weighted by using interval-valued intuitionistic hesitant 2-tuple fuzzy decision making and trial evaluation laboratory (DEMATEL). In the final stage, 9 different technical requirements are ranked by using interval-valued intuitionistic hesitant 2-tuple fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Additionally, another evaluation has also been conducted by considering Spherical fuzzy sets. Similarly, a comparative analysis has also been performed with VIKOR while ranking the alternatives. It is concluded that analysis results of both evaluations are quite similar. This situation gives an information about the coherency and consistency of the analysis results. The findings indicate that treatment services in noncommunicable diseases play the most significant role in this respect. Moreover, according to the ranking results, it is concluded that strategic policies should be related to improving the social security and special physician capacity as well as decreasing the out-of-pocket payment. Show more

Keywords: House of quality, UHC, hesitant linguistic terms, DEMATEL, TOPSIS

DOI: 10.3233/JIFS-202818

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2021

Authors: Sarraf, Gaurav | Srivatsa, Anirudh Ramesh | Swetha, MS

Article Type: Research Article

Abstract: With the ever-rising threat to security, multiple industries are always in search of safer communication techniques both in rest and transit. Multiple security institutions agree that any systems security can be modeled around three major concepts: Confidentiality, Availability, and Integrity. We try to reduce the holes in these concepts by developing a Deep Learning based Steganography technique. In our study, we have seen, data compression has to be at the heart of any sound steganography system. In this paper, we have shown that it is possible to compress and encode data efficiently to solve critical problems of steganography. The deep …learning technique, which comprises an auto-encoder with Convolutional Neural Network as its building block, not only compresses the secret file but also learns how to hide the compressed data in the cover file efficiently. The proposed techniques can encode secret files of the same size as of cover, or in some sporadic cases, even larger files can be encoded. We have also shown that the same model architecture can theoretically be applied to any file type. Finally, we show that our proposed technique surreptitiously evades all popular steganalysis techniques. Show more

Keywords: Cybersecurity, multimedia steganography, steganalysis, convolutional neural networks, cryptography

DOI: 10.3233/JIFS-189879

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Anushiadevi, R. | Amirtharajan, Rengarajan

Article Type: Research Article

Abstract: Reversible Data Hiding (RDH) schemes have recently gained much interest in protecting the secret information and sensitive cover images. For cloud security applications, the third party’s data embedding can be done (e.g., cloud service). In such a scenario, to protect the cover image from unauthorized access, it is essential to encrypt before embedding it. It can be overcome by combining the RDH scheme with encryption. However, the key challenge in integrating RDH with encryption is that the correlation between adjacent pixels begins to disappear after encryption, so reversibility cannot be accomplished. RDH with elliptic curve cryptography is proposed to overcome …this challenge. In this paper (ECC-RDH) by adopting additive homomorphism property; the proposed method, the stego image decryption gives the sum of the original image and confidential data. The significant advantages of this method are, the cover image is transferred with high security, the embedding capacity is 0.5 bpp with a smaller location map size of 0.05 bpp. The recovered image and secrets are the same as in the original, and thus 100% reversibility is proved. Show more

Keywords: Elliptic curve cryptography, reversible data hiding, additive homomorphism, lossless data hiding, reversible steganography

DOI: 10.3233/JIFS-189878

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Zhang, Shao-Yu

Article Type: Research Article

Abstract: This paper introduces a special Galois connection combined with the wedge-below relation. Furthermore, by using this tool, it is shown that the category of M -fuzzifying betweenness spaces and the category of M -fuzzifying convex spaces are isomorphic and the category of arity-2 M -fuzzifying convex spaces can be embedded in the category of M -fuzzifying interval spaces as a reflective subcategory.

Keywords: Fuzzy convex structure, fuzzy betweenness space, fuzzy interval space, arity-2 fuzzy convexity

DOI: 10.3233/JIFS-210060

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Liu, Peide | Khan, Qaisar | Mahmood, Tahir | Khan, Rashid Ali | Khan, Hidayat Ullah

Article Type: Research Article

Abstract: Pythagorean fuzzy set (PyFS) is an extension of various fuzzy concepts, such as fuzzy set (FS), intuitionistic FS, and it is enhanced mathematical gizmo to pact with uncertain and vague information. In this article, some drawbacks in the Dombi operational rules for Pythagorean fuzzy numbers (PyFNs) are examined and some improved Dombi operational laws for PyFNs are developed. We also find out that the value aggregated using the existing Dombi aggregation operators (DAOs) is not a PyFN. Furthermore, we developed two new aggregations, improved existing aggregation operators (AOs) for aggregating Pythagorean fuzzy information (PyFI) and are applied to multiple-attribute decision …making (MADM). To acquire full advantage of power average (PA) operators proposed by Yager, the Pythagorean fuzzy Dombi power average (PyFDPA) operator, the Pythagorean fuzzy Dombi weighted power average (PyFDWPA) operator, Pythagorean fuzzy Dombi power geometric (PyFDPG) operator, Pythagorean fuzzy Dombi weighted geometric (PyFDPWG) operator, improved the existing AOs and their desirable properties are discussed. The foremost qualities of these developed Dombi power aggregation operators is that they purge the cause of discomfited data and are more supple due to general parameter. Additionally, based on these Dombi power AOs, a novel MADM approach is instituted. Finally, a numerical example is given to show the realism and efficacy of the proposed approach and judgment with the existing approaches is also specified. Show more

Keywords: Pythagorean fuzzy set, PA operator, Dombi t-norm and Dombi t-conorm, MADM

DOI: 10.3233/JIFS-201723

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2021

Authors: Yang, Jie | Luo, Tian | Zhao, Fan | Li, Shuai | Jin, Xin

Article Type: Research Article

Abstract: Based on the granular computing and three-way decisions theory, the sequential three-way decisions (S3WD) model implements the idea of progressive computing. However, almost S3WD models are established based on labeled information system, and there is still a lack of S3WD model for processing unlabeled information system (UIS). In this paper, to solve the issue of given accepted number for UIS, a data-driven sequential three-way decisions (DDS3WD) model is proposed. Firstly, from the perspective of similarity computed by TOPSIS, a general three-way decisions model for UIS based on decision risk is presented and its shortcomings are analyzed. Then, a concept of …optimal density difference is defined to establish the DDS3WD model for UIS by updating attributes. Finally, the related experiments show that DDS3WD is feasible and effective for dealing with UIS under the condition of given accepted number of objects. Show more

Keywords: Sequential three-way decisions, unlabeled information system, data-driven, optimal density difference

DOI: 10.3233/JIFS-201527

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Alansari, Monairah | Shagari Mohammed, Shehu | Azam, Akbar

Article Type: Research Article

Abstract: As an improvement of fuzzy set theory, the notion of soft set was initiated as a general mathematical tool for handling phenomena with nonstatistical uncertainties. Recently, a novel idea of set-valued maps whose range set lies in a family of soft sets was inaugurated as a significant refinement of fuzzy mappings and classical multifunctions as well as their corresponding fixed point theorems. Following this new development, in this paper, the concepts of e -continuity and E -continuity of soft set-valued maps and α e -admissibility for a pair of such maps are introduced. Thereafter, we present some generalized quasi-contractions …and prove the existence of e -soft fixed points of a pair of the newly defined non-crisp multivalued maps. The hypotheses and usability of these results are supported by nontrivial examples and applications to a system of integral inclusions. The established concepts herein complement several fixed point theorems in the framework of point-to-set-valued maps in the comparable literature. A few of these special cases of our results are highlighted and discussed. Show more

Keywords: 46S40, 47H10, 54H25, e-soft fixed point, e-continuous, F-contraction, soft set-valued map, αe-admissible, integral inclusion

DOI: 10.3233/JIFS-202154

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021

Authors: Rajavel, Rajkumar | Ravichandran, Sathish Kumar | Nagappan, Partheeban | Venu, Sivakumar

Article Type: Research Article

Abstract: Maintaining the quality of service (QoS) related parameters is an important issue in cloud management systems. The lack of such QoS parameters discourages cloud users from using the services of cloud service providers. The proposed task scheduling algorithms consider QoS parameters such as the latency, make-span, and load balancing to satisfy the user requirements. These parameters cannot sufficiently guarantee the desired user experience or that a task will be completed within a predetermined time. Therefore, this study considered the cost-enabled QoS-aware task (job) scheduling algorithm to enhance user satisfaction and maximize the profit of commercial cloud providers. The proposed scheduling …algorithm estimates the cost-enabled QoS metrics of the virtual resources available from the unified resource layer in real-time. Moreover, the virtual machine (VM) manager frequently updates the current state-of-the art information about resources in the proposed scheduler to make appropriate decisions. Hence, the proposed approach guarantees profit for cloud providers in addition to providing QoS parameters such as make-span, cloud utilization, and cloud utility, as demonstrated through a comparison with existing time-and cost-based task scheduling algorithms. Show more

Keywords: Cloud computing, task scheduling, Qos aware task scheduling, cost enabled scheduling, cloud utilization, cloud utility

DOI: 10.3233/JIFS-189881

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Biswas, Kusan

Article Type: Research Article

Abstract: In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems  (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy …channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature. Show more

Keywords: Data hiding, JPEG, ECC, SVD, Turbo codes, PSNR, SSIM

DOI: 10.3233/JIFS-189877

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Ayub, Mohammed | El-Alfy, El-Sayed M.

Article Type: Research Article

Abstract: Web technology has become an indispensable part in human’s life for almost all activities. On the other hand, the trend of cyberattacks is on the rise in today’s modern Web-driven world. Therefore, effective countermeasures for the analysis and detection of malicious websites is crucial to combat the rising threats to the cyber world security. In this paper, we systematically reviewed the state-of-the-art techniques and identified a total of about 230 features of malicious websites, which are classified as internal and external features. Moreover, we developed a toolkit for the analysis and modeling of malicious websites. The toolkit has implemented several …types of feature extraction methods and machine learning algorithms, which can be used to analyze and compare different approaches to detect malicious URLs. Moreover, the toolkit incorporates several other options such as feature selection and imbalanced learning with flexibility to be extended to include more functionality and generalization capabilities. Moreover, some use cases are demonstrated for different datasets. Show more

Keywords: Web security, malicious websites, malicious URL, machine learning, feature extraction, toolkits

DOI: 10.3233/JIFS-189874

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021

Authors: Wang, Fubin | Liu, Peide | Wang, Peng

Article Type: Research Article

Abstract: A scientific evaluation model can be effectively used for the evaluation of regional talent development level. This paper proposes a set of scientific index systems for evaluating rural science and technology talents, which can be used for understanding the development status and level of rural science and technology talents in various regions; putting forward the corresponding talent cultivation and introduction policies, and; promoting the development of rural economic construction. Moreover, in order to avoid the shortcoming of over-subjective indicator weight in analytic hierarchy process (AHP), this paper uses the entropy weight method to determine indicator weight. Furthermore, giving the fact …that the evaluation experts may have individual personal preferences, this paper proposes an extended TODIM method based on hybrid index values, for achieving more scientific and effective evaluation results of rural science and technology talents. Finally, the proposed methods are evaluated on an actual case, where relevant analysis and suggestions are given. Show more

Keywords: Rural scientific and technological talents, TODIM method, entropy weight method, hybrid indicator, multi-attribute decision-making

DOI: 10.3233/JIFS-202847

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2021

Authors: Alpana, | Chand, Satish | Mohapatra, Subrajeet | Mishra, Vivek

Article Type: Research Article

Abstract: Coal is the mixture of organic matters, called as macerals, and inorganic matters. Macerals are categorized into three major groups, i.e., vitrinite, inertinite, and liptinite. The maceral group identification serves an important role in coking and non-coking coal processes that are used mainly in steel and iron industries. Hence, it becomes important to efficiently characterize these maceral groups. Currently, industries use the optical polarized microscope to distinguish the maceral groups. However, the microscopical analysis is a manual method which is time-consuming and provides subjective outcome due to human interference. Therefore, an automated approach that can identify the maceral groups accurately …in less processing time is strongly needed in industries. Computer-based image analysis methods are revolutionizing the industries because of its accuracy and efficacy. In this study, an intelligent maceral group identification system is proposed using markov-fuzzy clustering approach. This approach is an integration of fuzzy sets and the markov random field, which is employed towards maceral group identification in a clustering framework. The proposed model shows better results when compared with the standard cluster-based segmentation techniques. The results from the suggested model have also been validated against the outcome of manual methods, and the feasibility is tested using performance metrics. Show more

Keywords: Coal, macerals, image segmentation, clustering, fuzzy sets, markov random field

DOI: 10.3233/JIFS-189889

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2021

Authors: Richa, | Bedi, Punam

Article Type: Research Article

Abstract: Recommender System (RS) is an information filtering approach that helps the overburdened user with information in his decision making process and suggests items which might be interesting to him. While presenting recommendation to the user, accuracy of the presented list is always a concern for the researchers. However, in recent years, the focus has now shifted to include the unexpectedness and novel items in the list along with accuracy of the recommended items. To increase the user acceptance, it is important to provide potentially interesting items which are not so obvious and different from the items that the end user …has rated. In this work, we have proposed a model that generates serendipitous item recommendation and also takes care of accuracy as well as the sparsity issues. Literature suggests that there are various components that help to achieve the objective of serendipitous recommendations. In this paper, fuzzy inference based approach is used for the serendipity computation because the definitions of the components overlap. Moreover, to improve the accuracy and sparsity issues in the recommendation process, cross domain and trust based approaches are incorporated. A prototype of the system is developed for the tourism domain and the performance is measured using mean absolute error (MAE), root mean square error (RMSE), unexpectedness, precision, recall and F-measure. Show more

Keywords: Recommender system, cross domain, serendipity, trust, fuzzy sets

DOI: 10.3233/JIFS-189872

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Hamdoun, Hala | Sagheer, Alaa | Youness, Hassan

Article Type: Research Article

Abstract: Machine learning methods have been adopted in the literature as contenders to conventional methods to solve the energy time series forecasting (TSF) problems. Recently, deep learning methods have been emerged in the artificial intelligence field attaining astonishing performance in a wide range of applications. Yet, the evidence about their performance in to solve the energy TSF problems, in terms of accuracy and computational requirements, is scanty. Most of the review articles that handle the energy TSF problem are systematic reviews, however, a qualitative and quantitative study for the energy TSF problem is not yet available in the literature. The purpose …of this paper is twofold, first it provides a comprehensive analytical assessment for conventional, machine learning, and deep learning methods that can be utilized to solve various energy TSF problems. Second, the paper carries out an empirical assessment for many selected methods through three real-world datasets. These datasets related to electrical energy consumption problem, natural gas problem, and electric power consumption of an individual household problem. The first two problems are univariate TSF and the third problem is a multivariate TSF. Compared to both conventional and machine learning contenders, the deep learning methods attain a significant improvement in terms of accuracy and forecasting horizons examined. In the meantime, their computational requirements are notably greater than other contenders. Eventually, the paper identifies a number of challenges, potential research directions, and recommendations to the research community may serve as a basis for further research in the energy forecasting domain. Show more

Keywords: Energy time series forecasting, conventional forecasting methods, machine learning, deep learning, energy management systems

DOI: 10.3233/JIFS-201717

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-26, 2021

Authors: Zhang, Mu | Li, Si-si | Zhao, Bi-bin

Article Type: Research Article

Abstract: In view of the problem that it is difficult to quantitatively assess the interactivity between attributes in the identification process of 2-order additive fuzzy measure, this work uses the intuitionistic fuzzy sets (IFSs) to describe and deal with the interactivity between attributes. Firstly, the interactivity between attributes is defined by the supermodular game theory. On this basis, the experts employ the intuitionistic fuzzy number (IFN) to assess the interactivity between attributes, Secondly, the opinions of all experts are aggregated by using the intuitionistic fuzzy weighted average operator (IFWA). Finally, based on the aggregated results, the intuitionistic fuzzy interaction degree between …attributes is defined and calculated by the score function of IFN. Thus, a 2-order additive fuzzy measure identification method based on IFSs is further proposed. Based on the proposed method, using the Choquet fuzzy integral as nonlinear integration operator, a multi-attribute decision making (MADM) process is presented. Taking the credit evaluation of the big data listed companies in China as an application example, the feasibility and effectiveness of the proposed method is verified by the analysis results of application example. Show more

Keywords: Interactivity between attributes, intuitionistic fuzzy sets, 2-order additive fuzzy measure, choquet fuzzy integral, multi-attribute decision making, credit evaluation

DOI: 10.3233/JIFS-201368

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Jeena, R. S | Shiny, G. | Sukesh Kumar, A. | Mahadevan, K.

Article Type: Research Article

Abstract: Stroke is a major reason for disability and mortality in most of the developing nations. Early detection of stroke is highly significant in bio-medical research. Research illustrates that signs of stroke are reflected in the eye and may be analyzed from fundus images. A custom dataset of fundus images has been compiled for formulating an automated stroke detection algorithm. In this paper, a comparative study of hand-crafted texture features and convolutional neural network (CNN) has been recommended for stroke diagnosis. The custom CNN model has also been compared with five pre-trained models from ImageNet. Experimental results reveal that the recommended …custom CNN model gives the best performance by achieving an accuracy of 95.8 %. Show more

Keywords: Stroke, convolutional neural network (CNN)

DOI: 10.3233/JIFS-189855

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Shabir, Muhammad | Din, Jamalud | Ganie, Irfan Ahmad

Article Type: Research Article

Abstract: The original rough set model, developed by Pawlak depends on a single equivalence relation. Qian et al, extended this model and defined multigranulation rough sets by using finite number of equivalence relations. This model provide new direction to the research. Recently, Shabir et al. proposed a rough set model which depends on a soft relation from an universe V to an universe W  . In this paper we are present multigranulation roughness based on soft relations. Firstly we approximate a non-empty subset with respect to aftersets and foresets of finite number of soft binary relations. In this way we …get two sets of soft sets called the lower approximation and upper approximation with respect to aftersets and with respect to foresets. Then we investigate some properties of lower and upper approximations of the new multigranulation rough set model. It can be found that the Pawlak rough set model, Qian et al. multigranulation rough set model, Shabir et al. rough set model are special cases of this new multigranulation rough set model. Finally, we added two examples to illustrate this multigranulation rough set model. Show more

Keywords: Rough set, multigranulation rough set, soft set, soft relation and approximation by soft binary relation

DOI: 10.3233/JIFS-201910

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Luo, D. | Zhang, G.Z.

Article Type: Research Article

Abstract: The purpose of this paper is to solve the prediction problem of nonlinear sequences with multiperiodic features, and a multiperiod grey prediction model based on grey theory and Fourier series is established. For nonlinear sequences with both trend and periodic features, the empirical mode decomposition method is used to decompose the sequences into several periodic terms and a trend term; then, a grey model is used to fit the trend term, and the Fourier series method is used to fit the periodic terms. Finally, the optimization parameters of the model are solved with the objective of obtaining a minimum mean …square error. The novel model is applied to research on the loss rate of agricultural droughts in Henan Province. The average absolute error and root mean square error of the empirical analysis are 0.3960 and 0.5086, respectively. The predicted results show that the novel model can effectively fit the loss rate sequence. Compared with other models, the novel model has higher prediction accuracy and is suitable for the prediction of multiperiod sequences. Show more

Keywords: Nonlinear sequences, multiperiod, grey model, empirical mode decomposition, Fourier series

DOI: 10.3233/JIFS-202775

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Touqeer, Muhammad | Umer, Rimsha | Ali, Muhammad Irfan

Article Type: Research Article

Abstract: Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets are more proficient in handling uncertain and imprecise information than intuitionistic fuzzy sets and fuzzy sets. In this article, we put forward a chance-constraint programming method to solve linear programming network problems with interval-valued Pythagorean fuzzy constraints. This practice is developed using score function and upper and lower membership functions of interval-valued Pythagorean fuzzy numbers. The feasibility of the anticipated approach is illustrated by solving an airway network application and shown to be used to solve different types of network problems with objective function having interval-valued Pythagorean fuzzy numbers by employing it …on shortest path problem and minimum spanning tree problem. Furthermore, a comparative examination was performed to validate the effectiveness and usefulness of the projected methodology. Show more

Keywords: Interval-valued pythagorean fuzzy number (IVPFN), interval-valued trapezoidal pythagorean number (IVTrPFN), linear programming problem (LPP), chance-constraint programming (CCP)

DOI: 10.3233/JIFS-202383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2021

Authors: Zhang, Yongjie | Cao, Kang | Liang, Ke | Zeng, Yongqi

Article Type: Research Article

Abstract: Commonality, a typical commercial feature of serialized civil aircraft study and development, refers to a series of methods of reusing and sharing assets, which were developed based on broad similarity. The common design of serialized civil aircraft is capable of maximally saving R&D, production, operation, and disposal. To maximize the total benefits of manufacturers and operators, the common design of serialized civil aircrafts primarily exploits the commercial experience of serialized products in other fields (e.g., automobiles and mobile phones), whereas a scientific index system and quantitative evaluation model has not been formed. Accordingly, this study proposes a new civil aircraft …commonality index evaluation model in accordance with fuzzy set theory and methods. The model follows two branches, i.e., attribute commonality and structural commonality, to develop a multi-level civil aircraft commonality index system. The proposed model can split the commonality into six commonality sub-intervals and build the corresponding standard fuzzy set with the characteristic attribute parameters of the civil aircraft as the elements. Next, based on considerable civil aircraft sample data, a fuzzy test is designed to yield the membership function of the fuzzy set. Thus, a model of evaluating civil aircraft commonality is constructed, taking the characteristic parameters of the civil aircraft to be evaluated as input, and selecting the degree of commonality of each level as output. Lastly, this study employs the evaluation model to evaluate the commonality of Boeing 757-200 with other civil aircrafts. Furthermore, the evaluated results well explain the actual situation, which verifies the effectiveness and practicability of the proposed model. Show more

Keywords: Cost benefit analysis, serialized civil aircraft, commonality index, fuzzy set, membership function

DOI: 10.3233/JIFS-202749

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2021

Authors: Pathak, Vinay | Singh, Karan

Article Type: Research Article

Abstract: Due to the rapid growth in sensor technology and embedded technology, wireless body area network WBANs plays a vital role in monitoring the human body system and the surrounding environment. It supports many healthcare applications on the one hand and are very much help full in pandemic scenarios. It has become the most innovative health care area, which is intriguing to many researchers because of its vast future prospective and potential. Data collected by different wireless sensors or nodes is very personal, critical, and important because of human life involvement. WBANs can minimize human to human contact, which helps stop …the spread of severe infectious diseases. The biggest concern is the maintenance of privacy and accuracy of data is still a hot area of research due to nature of attacks, which are changing day by day and increasing, as well as for the sake of better performance. A suitable security mechanism is a way to address above issues, for achieving data security, it is expedient to propose a mechanism. It is essential to update the patient’s regular data. WBANs help to deliver truthful reports related to the patient’s health regularly and individually. This paper proposes an algorithm that shows a better result than the existing algorithm in their previous works. This work is all about proposing a mechanism which needs comparatively less resource. Only authentic entities can interact with the server, which has become obligatory for both sides, keeping data safe. Several authentication schemes have been proposed or discussed by different researchers. This paper has proposed a Secure and Efficient WBANs Authentication Mechanism (SEAM). This security framework will take care of the authentication and the security of transmitted data. Show more

Keywords: WBANs, wearable sensors, eHealth privacy & security, threat, WSN, security

DOI: 10.3233/JIFS-189873

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Dhanani, Jenish | Mehta, Rupa | Rana, Dipti

Article Type: Research Article

Abstract: Legal practitioners analyze relevant previous judgments to prepare favorable and advantageous arguments for an ongoing case. In Legal domain, recommender systems (RS) effectively identify and recommend referentially and/or semantically relevant judgments. Due to the availability of enormous amounts of judgments, RS needs to compute pairwise similarity scores for all unique judgment pairs in advance, aiming to minimize the recommendation response time. This practice introduces the scalability issue as the number of pairs to be computed increases quadratically with the number of judgments i.e., O  (n 2 ). However, there is a limited number of pairs consisting of strong relevance among …the judgments. Therefore, it is insignificant to compute similarities for pairs consisting of trivial relevance between judgments. To address the scalability issue, this research proposes a graph clustering based novel Legal Document Recommendation System (LDRS) that forms clusters of referentially similar judgments and within those clusters find semantically relevant judgments. Hence, pairwise similarity scores are computed for each cluster to restrict search space within-cluster only instead of the entire corpus. Thus, the proposed LDRS severely reduces the number of similarity computations that enable large numbers of judgments to be handled. It exploits a highly scalable Louvain approach to cluster judgment citation network, and Doc2Vec to capture the semantic relevance among judgments within a cluster. The efficacy and efficiency of the proposed LDRS are evaluated and analyzed using the large real-life judgments of the Supreme Court of India. The experimental results demonstrate the encouraging performance of proposed LDRS in terms of Accuracy, F1-Scores, MCC Scores, and computational complexity, which validates the applicability for scalable recommender systems. Show more

Keywords: Legal document recommender systems, Pairwise similarity, Graph Clustering, Semantic similarity

DOI: 10.3233/JIFS-189871

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Naderi, Katayoun | Ahari, Roya M. | Jouzdani, Javid | Amindoust, Atefeh

Article Type: Research Article

Abstract: Fierce competition in the global markets forced companies to improve the design and management of supply chains, because companies are always looking for more profit and higher customer satisfaction. The emergence of the green supply chain is one of the most important developments of the last decade. It provides an opportunity for companies to adjust their supply chains according to environmental goals and sustainability. The integrated production-inventory-routing is a new field that aims to optimize these three decision-making levels. It can be described as follow: a factory produces one or more products, and sells them to several customers (by direct …delivery or a specific customer chain). The current study aims to model a production-inventory-routing system using a system dynamics approach to design a green supply chain under uncertain conditions. For this purpose, first, the association between selected variables was determined. Then, the proposed model was validated. Finally, to identify variables with the highest influence, four scenarios were developed. The results indicated that minimum total transportation cost, the total warehouse capacity of the supply chain, and the maximum production rate are the most influential strategies to achieve ideal condition. Show more

Keywords: System dynamics, integrated production-inventory-routing problem, green supply chain, uncertainty

DOI: 10.3233/JIFS-202622

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2021

Authors: Zhang, Kai | Zheng, Jing | Wang, Ying-Ming

Article Type: Research Article

Abstract: Case-based reasoning (CBR) is one of the most popular methods used in emergency decision making (EDM). Case retrieval plays a key role in EDM processes based on CBR and usually functions by retrieving similar historical cases using similarity measurements. Decision makers (DMs), thus, choose the most appropriate historical cases. Although uncertainty and fuzziness are present in the EDM process, in-depth research on these issues is still lacking. In this study, a heterogeneous multi-attribute case retrieval method based on group decision making (GDM) with incomplete weight information is developed. First, the case similarities between historical and target cases are calculated, and …a set of similar historical cases is constructed. Six formats of case attributes are considered, namely crisp numbers, interval numbers, linguistic variables, intuitionistic fuzzy numbers, single-valued neutrosophic numbers (NNs) and interval-valued NNs. Next, the evaluation information from the DMs is expressed using single-valued NNs. Additionally, the evaluation utilities of similar historical cases are obtained by aggregating the evaluation information. The comprehensive utilities of similar historical cases are obtained using case similarities and evaluation utilities. In this process, the weights of incomplete information are determined by constructing optimization models. Furthermore, the most appropriate similar historical case is selected according to the comprehensive utilities. Finally, the proposed method is demonstrated using two examples; its performance is then compared with those of other similar methods to demonstrate its validity and efficacy. Show more

Keywords: Case retrieval, group decision making, single-valued neutrosophic number, incomplete weight information, emergency decision making

DOI: 10.3233/JIFS-201817

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Lalitha, S. | Gupta, Deepa

Article Type: Research Article

Abstract: Automatic recognition of human affective state using speech has been the focus of the research world for more than two decades. In the present day, with multi-lingual countries like India and Europe, population are communicating in various languages. However, majority of the existing works have put forth different strategies to recognize affect from various databases, with each comprising single language recordings. There exists a great demand for affective systems to serve the context of mixed-language scenario. Hence, this work focusses on an effective methodology to recognize human affective state using speech samples from a mixed language framework. A unique cepstral …and bi-spectral speech features derived from the speech samples classified using random forest (RF) are applied for the task. This work is first of its kind with the proposed approach validated and found to be effective on a self-recorded database with speech samples comprising from eleven various diverse Indian languages. Six different affective states of angry, fear, sad, neutral, surprise and happy are considered. Three affective models have been investigated in the work. The experimental results demonstrate the proposed feature combination in addition to data augmentation show enhanced affect recognition. Show more

Keywords: Affective state, cepstral, mixed-lingual, recognition, Indian languages

DOI: 10.3233/JIFS-189868

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Jithendra, K.B. | Kassim, Shahana T.

Article Type: Research Article

Abstract: Security of a recently proposed bitwise block cipher GIFT is evaluated in this paper. In order to mount full round attacks on the cipher, biclique cryptanalysis method is applied. Both variants of the block cipher are attacked using Independent biclique approach. For recovering the secret keys of GIFT-64, the proposed attack requires 2127.45 full GIFT-64 encryption and 28 chosen plain texts. For recovering the secret keys of GIFT-128, the proposed attack requires 2127.82 full GIFT-128 encryption and 218 chosen plain texts. The attack complexity is compared with that of other attacks proposed previously. The security level …of GIFT is also compared with that of the parent block cipher PRESENT, based on the analysis. Show more

Keywords: Block cipher, cryptanalysis, biclique, complexity

DOI: 10.3233/JIFS-189875

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Cai, LiHua | Cao, Jin | Wang, MingQiang | Zhou, Ta | Fang, HaiFeng

Article Type: Research Article

Abstract: Both classification rate and accuracy are crucial for the recyclable PET bottles, and the existing combination methods of SVM all simply use SVM as the unit classifier, ignoring the improvement of SVM’s classification performance in the training process of deep learning. A linear multi hierarchical deep structure based on Support Vector Machine (SVM) is proposed to cover this problem. A novel definition of the input matrix in each layer enhances the optimization of Lagrange multipliers in Sequential Minimal Optimization (SMO) algorithm, thus the datapoint in maximum interval of SVM hyperplane could be recognized, improving the classification performance of SVM classifier …in this layer. The loss function defined in this paper could control the depth of Linear Multi Hierarchical SVM (LMHSVM), the generalization parameters are added in the loss function and the input matrix to enhance the generalization performance of LMHSVM. The process of creating Bottle dataset by Histogram of Oriented Gradient (HOG) and Principal Component Analysis (PCA) is introduced meanwhile, reducing the data size of bottles. Experiments are conducted on LMHSVM and multiple typical classification algorithms with Bottle dataset and UCI datasets, the results indicated that LMHSVM has excellent classification performances than FNN classifier, LIBSVM (Gaussian) and GFS-AdaBoost-C in KEEL. Show more

Keywords: Recycling plastic bottles, deep learning structure, SVM, Linear multi hierarchical, extract dataset

DOI: 10.3233/JIFS-202729

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2021

Authors: Pavan Kumar, C S | Dhinesh Babu, L D

Article Type: Research Article

Abstract: Sentiment analysis is widely used to retrieve the hidden sentiments in medical discussions over Online Social Networking platforms such as Twitter, Facebook, Instagram. People often tend to convey their feelings concerning their medical problems over social media platforms. Practitioners and health care workers have started to observe these discussions to assess the impact of health-related issues among the people. This helps in providing better care to improve the quality of life. Dementia is a serious disease in western countries like the United States of America and the United Kingdom, and the respective governments are providing facilities to the affected people. …There is much chatter over social media platforms concerning the patients’ care, healthy measures to be followed to avoid disease, check early indications. These chatters have to be carefully monitored to help the officials take necessary precautions for the betterment of the affected. A novel Feature engineering architecture that involves feature-split for sentiment analysis of medical chatter over online social networks with the pipeline is proposed that can be used on any Machine Learning model. The proposed model used the fuzzy membership function in refining the outputs. The machine learning model has obtained sentiment score is subjected to fuzzification and defuzzification by using the trapezoid membership function and center of sums method, respectively. Three datasets are considered for comparison of the proposed and the regular model. The proposed approach delivered better results than the normal approach and is proved to be an effective approach for sentiment analysis of medical discussions over online social networks. Show more

Keywords: Dementia, sentiment analysis, machine learning, FDA, feature-split, feature engineering, trapezoid membership function

DOI: 10.3233/JIFS-202874

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021