Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Wang, Guan | Wu, Lingjiu | Liu, Yusheng | Ye, Xiaoping

Article Type: Research Article

Abstract: With the rise of group decision-making and the increasingly complex decision-making environment, preference modeling for decision makers has become more and more important, and many preference modeling methods have emerged. Based on the fuzzy theory, researchers have proposed a large number of preference models to express the subjective uncertainty of decision makers. These methods based on fuzzy theory are collectively referred to as fuzzy preference modeling methods. The fuzzy sets preference model is the first practice of fuzzy theory used in the field of preference modeling, and it is still widely used by researchers until now. Subsequently, based on fuzzy …theory, the researchers also proposed linguistic term sets and cloud model. These methods have different representation domains, and are applicable to different decision-making environment. In this paper we give a review of classical fuzzy preference modeling methods and its latest extensions and variants. After the presentation of comparative analyses on the existing methods, we figure out some current challenges and possible future development directions in the field of fuzzy preference modeling. Show more

Keywords: Preference modeling, fuzzy preference modeling, fuzzy sets, group decision-making, decision-making modeling

DOI: 10.3233/JIFS-201529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10645-10660, 2021

Authors: Al-Khayyat, Kamal | Al-Shaikhli, Imad | Al-Hagery, Mohammed

Article Type: Research Article

Abstract: This paper details the examination of a particular case of data compression, where the compression algorithm removes the redundancy from data, which occurs when edge-based compression algorithms compress (previously compressed) pixelated images. The newly created redundancy can be removed using another round of compression. This work utilized the JPEG-LS as an example of an edge-based compression algorithm for compressing pixelated images. The output of this process was subjected to another round of compression using a more robust but slower compressor (PAQ8f). The compression ratio of the second compression was, on average,  18%, which is high for random data. The results …of the second compression were superior to the lossy JPEG. Under the used data set, lossy JPEG needs to sacrifice  10% on average to realize nearly total lossless compression ratios of the two-successive compressions. To generalize the results, fast general-purpose compression algorithms (7z, bz2, and Gzip) were used too. Show more

Keywords: Data compression, lossless, lossy, Pixelated images, PAQ8f

DOI: 10.3233/JIFS-201563

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10661-10669, 2021

Authors: Wu, Jian-Zhang | Beliakov, Gleb

Article Type: Research Article

Abstract: Nonmodularity is a prominent property of capacity that deeply links to the internal interaction phenomenon of multiple decision criteria. Following the common architectures of the simultaneous interaction indices as well as of the bipartition interaction indices, in this paper, we construct and study the notion of probabilistic nonmodularity index and also its particular cases, such as Shapely and Banzhaf nonmodularity indices, which can be used to describe the comprehensive interaction situations of decision criteria. The connections and differences among three categories of interaction indices are also investigated and compared theoretically and empirically. It is shown that three types of interaction …indices have the same roots in their first and second orders, but meanwhile the nonmodularity indices have involved less amount of subsets and can be adopted to describe the interaction phenomenon in decision analysis. Show more

Keywords: Fuzzy measure, interaction representation, nonmodularity, nonadditivity, decision analysis

DOI: 10.3233/JIFS-201583

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10671-10685, 2021

Authors: Sabahi, Farnaz | Akbarzadeh–T., Mohammad-R.

Article Type: Research Article

Abstract: It would be hard to deny the importance of fuzzy number ranking in fuzzy-based applications. The definition of fuzzy ranking, however, evades an easy description due to the overlapping of fuzzy sets. While many researchers have addressed this subject, close examination reveals that their results suffer from one or more shortcomings such as image-ranking problems or ranking two equally embedded fuzzy numbers with the same centroid and different spreads. This paper proposes a new fast and straightforward computational approach to ranking fuzzy numbers that aims to overcome such problems. The proposed approach considers several important factors such as spread, skewness …and center, in addition to human intuition. Further, the proposed ranking approach involves a composition of these factors as demonstrated in the several examples provided and in comparison with other existing approaches. Show more

Keywords: Center, human intuition, skewness, spread, ranking fuzzy numbers

DOI: 10.3233/JIFS-201591

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10687-10701, 2021

Authors: Shobana, J. | Murali, M.

Article Type: Research Article

Abstract: Text Sentiment analysis is the process of predicting whether a segment of text has opinionated or objective content and analyzing the polarity of the text’s sentiment. Understanding the needs and behavior of the target customer plays a vital role in the success of the business so the sentiment analysis process would help the marketer to improve the quality of the product as well as a shopper to buy the correct product. Due to its automatic learning capability, deep learning is the current research interest in Natural language processing. Skip-gram architecture is used in the proposed model for better extraction of …the semantic relationships as well as contextual information of words. However, the main contribution of this work is Adaptive Particle Swarm Optimization (APSO) algorithm based LSTM for sentiment analysis. LSTM is used in the proposed model for understanding complex patterns in textual data. To improve the performance of the LSTM, weight parameters are enhanced by presenting the Adaptive PSO algorithm. Opposition based learning (OBL) method combined with PSO algorithm becomes the Adaptive Particle Swarm Optimization (APSO) classifier which assists LSTM in selecting optimal weight for the environment in less number of iterations. So APSO - LSTM ‘s ability in adjusting the attributes such as optimal weights and learning rates combined with the good hyper parameter choices leads to improved accuracy and reduces losses. Extensive experiments were conducted on four datasets proved that our proposed APSO-LSTM model secured higher accuracy over the classical methods such as traditional LSTM, ANN, and SVM. According to simulation results, the proposed model is outperforming other existing models. Show more

Keywords: Sentimental analysis, adaptive particle swarm optimization, LSTM, skip-gram, feature extraction

DOI: 10.3233/JIFS-201644

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10703-10719, 2021

Authors: Tham, Tran Thi | Doan, Linh Thi Truc | Amer, Yousef | Lee, Sang Heon

Article Type: Research Article

Abstract: Operation strategy plays an important role in business improvement and calls for many research attention in recent years. This study aims to propose an integrated approach to determine the most appropriate operational strategies in their companies under multi-conflicting objectives with a limited budget. The novel approach is developed by using the combination of Fuzzy Technique for Order Preference by Similarity to Ideal Situation (Fuzzy TOPSIS), Sensitivity Analysis (SA) and Multi-Objective Linear Programming (MOLP) model. The operation strategies are evaluated through five objectives such as Productivity, Quality, Cost, Time and Importance score. The importance scores of all strategies are firstly obtained …from the Fuzzy TOPSIS method. The sets of the weight of criteria are then established by using SA while MOLP approach is used to select appropriate strategies under multi-conflicting objectives with limited resources. A case study with 110 possible scenarios of operational strategies from An Giang Fisheries Import Export Joint Stock Company in Vietnam is considered to illustrate the practicability of the proposed approach. The results found that the proposed approach is suitable to make a decision on operation strategy. Show more

Keywords: Fuzzy TOPSIS, operation strategy, strategy selection, sensitivity analysis, multi-objective linear Programming model (MOLP)

DOI: 10.3233/JIFS-201688

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10721-10736, 2021

Authors: Ayvaz-Çavdaroğlu, Nur

Article Type: Research Article

Abstract: Agriculture is a crucial and strategic sector for developing countries. The agricultural sector in Turkey has been suffering from regression in recent years due to several reasons. In an attempt to reverse this process, we analyze the cultivation possibilities of high profit-margin crops in Turkish lands and develop a ranking among eight alternative crops. To perform a comprehensive analysis encompassing several dimensions, three MCDM methods are utilized; namely fuzzy AHP to determine the weights of evaluation criteria, and TOPSIS and PROMETHEE to develop a ranking among the crop alternatives. The crop alternatives are evaluated against several economic, technical, social and …environmental criteria. The results favor the cultivation of soy bean, goji berry and buckwheat, while tamarind appears to be the least favored crop among the considered alternatives. The analysis results are enhanced with a sensitivity analysis. Show more

Keywords: Multi criteria decision making, fuzzy AHP, TOPSIS, PROMETHEE, agricultural planning, sensitivity analysis

DOI: 10.3233/JIFS-201701

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10737-10749, 2021

Authors: Dhanaraj, Rajesh Kumar | Lalitha, K. | Anitha, S. | Khaitan, Supriya | Gupta, Punit | Goyal, Mayank Kumar

Article Type: Research Article

Abstract: In Wireless Sensor Networks (WSNs), effective transmission with acceptable degradation in the power of sensor nodes is a key challenge. In a large network, holdup is bound to occur in communicating superfluous data. The aforementioned issues namely, energy, delay and data redundancy are interdependent on each other and a tradeoff needs to be worked out to improve the overall performance. The extant methods in the literature employ either centralized or distributed approach to select a cluster head (CH). In this paper, sink originated hybrid and dynamic clustering with routing technique is proposed. The proposed routing algorithm works based on node …handling capability of each sensor node in the selection of CH and also helps in identifying the forwarder node. In addition, processing load of a sensor node is also considered for selecting the forwarder. Both space and time correlation is used to collect data from the clusters and then aggregated to provide a proficient communication. The introduced method is evaluated with the performance of the previously available techniques like, Data Routing for In-Network Aggregation (DRINA), Efficient Data Collection Aware of Spatio-Temporal Correlation (EAST), Cluster-Based Data Aggregation (CBDA), Energy-Efficient Data Aggregation and Transfer (EEDAT), and Distributed algorithm for Integrated tree Construction and data Aggregation (DICA). Simulation parameters considered for assess ing the performance of the proposed algorithm are aggregation ratio, routing overhead, packet delivery fraction, throughput, packet delay and consumed energy. The experimental analysis of the introduced algorithm generates paramount outcome of finest aggregation quality with diverse key characteristics and circumstances as required by a sensor network. Show more

Keywords: Wireless sensor networks, clustering algorithms, spatio-temporal phenomena, correlation routing, energy efficiency

DOI: 10.3233/JIFS-201756

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10751-10765, 2021

Authors: Ramírez-Mendoza, Abigail María Elena | Yu, Wen | Li, Xiaoou

Article Type: Research Article

Abstract: The identification of nonlinear systems is a complex task. This article presents a method comparison between the new Fuzzy Adaptive Neurons (FAN), Radial Basis Function Network (RBF), and Adaptive Network-Based Fuzzy Inference System (ANFIS). The nonlinear systems presented are solved with stable and optimal learning. The simulation of the results for two models presented, are carried out in Matlab® , the optimization of the system identification for the first and second systems were obtained with great success.

Keywords: Fuzzy adaptive neurons, identification of systems, learning algorithm, level sets, ANFIS, nonlinear systems

DOI: 10.3233/JIFS-201782

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10767-10779, 2021

Authors: Yu, Xin | Zeng, Feng | Mwakapesa, Deborah Simon | Nanehkaran, Y.A. | Mao, Yi-Min | Xu, Kai-Bin | Chen, Zhi-Gang

Article Type: Research Article

Abstract: The main target of this paper is to design a density-based clustering algorithm using the weighted grid and information entropy based on MapReduce, noted as DBWGIE-MR, to deal with the problems of unreasonable division of data gridding, low accuracy of clustering results and low efficiency of parallelization in big data clustering algorithm based on density. This algorithm is implemented in three stages: data partitioning, local clustering, and global clustering. For each stage, we propose several strategies to improve the algorithm. In the first stage, based on the spatial distribution of data points, we propose an adaptive division strategy (ADG) to …divide the grid adaptively. In the second stage, we design a weighted grid construction strategy (NE) which can strengthen the relevance between grids to improve the accuracy of clustering. Meanwhile, based on the weighted grid and information entropy, we design a density calculation strategy (WGIE) to calculate the density of the grid. And last, to improve the parallel efficiency, core clusters computing algorithm based on MapReduce (COMCORE-MR) are proposed to parallel compute the core clusters of the clustering algorithm. In the third stage, based on disjoint-set, we propose a core cluster merging algorithm (MECORE) to speed-up ratio the convergence of merged local clusters. Furthermore, based on MapReduce, a core clusters parallel merging algorithm (MECORE-MR) is proposed to get the clustering algorithm results faster, which improves the core clusters merging efficiency of the density-based clustering algorithm. We conduct the experiments on four synthetic clusters. Compared with H-DBSCAN, DBSCAN-MR and MR-VDBSCAN, the experimental results show that the DBWGIE-MR algorithm has higher stability and accuracy, and it takes less time in parallel clustering. Show more

Keywords: Big data, density-based clustering algorithm, weighted grid, information entropy

DOI: 10.3233/JIFS-201792

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10781-10796, 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. 40, no. 6, pp. 10797-10809, 2021

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

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. 40, no. 6, pp. 10811-10824, 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. 40, no. 6, pp. 10825-10836, 2021

Authors: Hu, Limei | Tan, Chunqiao | Deng, Hepu

Article Type: Research Article

Abstract: With the changing business environment and the active participation of various stakeholders in the decision making process, it plays an increasingly important role to the weight of decision makers and the preference information given by decision makers. This paper presents a novel approach for group decision making under uncertainty with the involvement of the third-party evaluator in the decision making process. Recognizing the challenge in adequately determining the weight of decision makers in group decision making, the evidence theory is appropriately used with the involvement of the third-party evaluator. To effectively model the uncertainty and imprecision in the decision making …process, fuzzy preference relations are used for better representing the subjective assessment of individual decision makers. To adequately determine the ranking of available alternatives, the logarithmic least square method is applied for appropriately aggregating the fuzzy preference relation of individual decision makers. A group consensus index is developed for facilitating consensus building in group decision making. This leads to better group decisions being made. A real-world application is presented that shows the proposed approach is effective in solving group decision making problems under uncertainty. Show more

Keywords: Group decision making, uncertainty modeling, fuzzy numbers

DOI: 10.3233/JIFS-201846

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10837-10851, 2021

Authors: Mao, Hua | Liu, Xiaoqing | Wang, Gang

Article Type: Research Article

Abstract:  Semiconcept, a new data processing model, enriches the development of formal concept analysis. However, the classical semiconcept is supported by two-way decisions. In the study of classical semiconcept theory, how to express the information of jointly not possessed is also essential in making decisions. Therefore, this paper tries to combine the classical semiconcept theory with three-way decisions to present three-way semiconcepts, and carry on the further study. Firstly, we define new operators and give some properties of them. Two kinds of three-way semiconcepts —OE-semiconcept and AE-semiconcept, are presented. And the corresponding structures are searched out from the perspective of lattice …theory. Furthermore, we analyze the relationship among three-way concepts, three-way semiconcepts and classical semiconcepts. On this basis, the algorithms to build OE-semiconcept and AE-semiconcept are presented. At the meanwhile, we take some examples to examine and explain the obtained results. Show more

Keywords: Semiconcept, Formal concept analysis, Three-way decisions, Three-way semiconcepts, Lattice

DOI: 10.3233/JIFS-201862

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10853-10864, 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. 40, no. 6, pp. 10865-10876, 2021

Authors: Aşıcı, Emel

Article Type: Research Article

Abstract: In this paper, we give construction methods for triangular norms (t-norms) and triangular conorms (t-conorms) on appropriate bounded lattices. Then, we compare our methods and well-known methods proposed in [2, 8, 19 ]. Finally, we give different construction methods for t-norms and t-conorms on an appropriate bounded lattice by using recursion. Also, we provide some examples to discuss introduced methods.

Keywords: Triangular norms, triangular conorms, ordinal sum, bounded lattice

DOI: 10.3233/JIFS-201899

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10877-10892, 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. 40, no. 6, pp. 10893-10908, 2021

Authors: Gholi Beik, Adeleh Jafar | Shiri Ahmad Abadib, Mohammad Ebrahim | Rezakhani, Afshin

Article Type: Research Article

Abstract: Today, due to increasing dependence on the internet, the tendency to make smart and the Internet of things (IoT), has risen. Also, detecting attacks, and malicious activity as well as anomalies on the internet networks, and preventing them from different layers is a necessity. In this method, a new hybrid model of IWC clustering and Random Forest methods are introduced to identify normal and abnormal conditions. It also shows unauthorized access and attacks to different layers of the Internet of Things, especially the application layer. The IWC is a clustering and improved model of the k-means method. After being tested, …evaluated, and compared with previous methods, the proposed model indicates that identifying anomalies in, its data has been efficient and useful. Unlabeled data from the Intel data set IBRL is used to cluster its input data. The NSL-KDD data set is also used in the proposed method to select the best classification and identify attacks on the network. Show more

Keywords: Anomaly detection, application layer, classification algorithms, inversely weight clustering (IWC), cloud computing

DOI: 10.3233/JIFS-201938

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10909-10918, 2021

Authors: Lin, Qiongbin | Xu, Zhifan | Lin, Chih-Min

Article Type: Research Article

Abstract: This study proposes the novel method of lithium-ion battery state of health (SoH) estimation and remaining useful life (RUL) prediction to ensure the safety and reliability of the energy storage system. A fuzzy brain emotional learning neural network (FBELNN) is employed to estimate SoH and a recurrent cerebellar model neural network (RCMNN) is used for the RUL prediction. The inputs of FBELNN are extracted features from the monitoring curve of the constant voltage and current, because the lithium-ion battery is seldom completely discharged and the discharging situation in actual operating process is complex. The FBELNN learns the battery aging features …that are extracted and selected by discrete wavelet transform and principal component analysis, respectively. The SoH estimation results from the FBELNN are accurate due to the special structure and parameters adaptive laws. The RCMNN and online training again can improve the performance of RUL prediction, because recurrent units can capture the dynamic features. Experimental data are performed by using NASA Prognostics Center of Excellence battery datasets to verify the effectiveness of the proposed method. The results show that the root mean square error of SoH estimation is smaller by the FBELNN and the prediction accuracy of RUL is higher by RCMNN under the different starting points. Show more

Keywords: Fuzzy brain emotional learning neural network, recurrent cerebellar model neural network, lithium-ion battery, remaining useful life, state of health

DOI: 10.3233/JIFS-201952

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10919-10933, 2021

Authors: Li, Hongyan | Wu, Peng | Zhou, Ligang | Chen, Huayou

Article Type: Research Article

Abstract: The consensus problem is a very important aspect of group decision making (GDM). In order to deal with the multiple criteria group decision consensus problem in the interval type-2 fuzzy environment, a consensus measure based on similarity measurement is proposed in this paper. In this paper, first, a new similarity measure of two interval type-2 fuzzy sets (IT2FSs) is defined and the consensus measure is defined by the similarity measure between two IT2FSs. Then, a new consensus feedback mechanism is proposed. In the stage of alternatives selection, the entropy of IT2FSs is defined, and the entropy weight method is used …to determine the weights of the criteria. Finally, the feasibility of the method proposed in this paper is illustrated by a comprehensive evaluation of old-age institutions. Show more

Keywords: IT2FSs, similarity measure, consensus, MCGDM

DOI: 10.3233/JIFS-201979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10935-10953, 2021

Authors: Ayidzoe, Mighty Abra | Yu, Yongbin | Mensah, Patrick Kwabena | Cai, Jingye | Kwabena, Adu | Tashi, Nyima

Article Type: Research Article

Abstract: Availability of massive amounts of data is a key contributing factor that influences the performance of deep learning models. Convolutional Neural Networks for instance, require large amounts of data in different variations to enable them generalize well to viewpoints. However, in health and other application domains, data generation and processing tasks are time-consuming and requires annotation by experts. Capsule Network (CapsNet) have been proposed to curtail the limitations of Convolutional Neural Networks (CNNs). Due to the problem of crowding, capsule Networks perform badly on complex and real-life images such as CIFAR 10 and some medical images. In this study, a …variant of a capsule network with a new algorithm referred to as the amplifier and a new squash function termed exponential squash is proposed. The amplifier is implemented in the encoder network to improve the texture of the images and has the ability to assign low relevance to irrelevant features and high relevance to vital features. The exponential squash function reduces the coupling strength of unrelated capsules in the lower and upper capsule layer. The proposed algorithm was evaluated on four datasets; CIFAR 10, fashion-MNIST, eye disease dataset and ODIR dataset achieving accuracies of 84.56% 93.76%, 89.02% and 87.27% respectively. This work sheds light on the possibility of applying CapsNet on complex real-world tasks. The proposed model can serve as an intelligent tool to aid medical personnel to diagnose eye disease and apply the necessary treatments. Show more

Keywords: Capsule network, convolutional neural network, squash function, feature amplification

DOI: 10.3233/JIFS-202080

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10955-10968, 2021

Authors: Zhou, Wang | Yang, Yujun | Du, Yajun | Haq, Amin Ul

Article Type: Research Article

Abstract: Recent researches indicate that pairwise learning to rank methods could achieve high performance in dealing with data sparsity and long tail distribution in item recommendation, although suffering from problems such as high computational complexity and insufficient samples, which may cause low convergence and inaccuracy. To further improve the performance in computational capability and recommendation accuracy, in this article, a novel deep neural network based recommender architecture referred to as PDLR is proposed, in which the item corpus will be partitioned into two collections of positive instances and negative items respectively, and pairwise comparison will be performed between the positive instances …and negative samples to learn the preference degree for each user. With the powerful capability of neural network, PDLR could capture rich interactions between each user and items as well as the intricate relations between items. As a result, PDLR could minimize the ranking loss, and achieve significant improvement in ranking accuracy. In practice, experimental results over four real world datasets also demonstrate the superiority of PDLR in contrast to state-of-the-art recommender approaches, in terms of Rec@N, Prec@N, AUC and NDCG@N. Show more

Keywords: Pairwise comparison, neural network, learning to rank, item recommendation

DOI: 10.3233/JIFS-202092

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10969-10980, 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. 40, no. 6, pp. 10981-10998, 2021

Authors: Li, Sizhao | Han, Xinyu | Bi, Lvqing | Hu, Bo | Dai, Songsong

Article Type: Research Article

Abstract: Complex fuzzy aggregation operation (CFAO) is a formalized definition of combining several complex fuzzy sets into a single complex fuzzy set. It extends classical fuzzy aggregation operation (FAO) to the complex-valued domain retaining classical real-valued weight. CFAO was initially defined with complex weight by Ramot et al. However, there has been virtually no progress in developing CFAO with complex weight. In this paper, we study the CFAOs with complex weight. We first discuss how to define complex weights meeting the restriction that the sum of weights is equal to 1. We give a new natural type of complex weight which …is different from Ramot et al.’s complex weight. Then we study various properties which include idempotency, homogeneity, rotational invariance and shift invariance for CFAOs with both types of complex weights. Show more

Keywords: Complex fuzzy sets, complex fuzzy aggregation, complex weight, invariance properties

DOI: 10.3233/JIFS-202100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10999-11005, 2021

Authors: Yu, Xiaobing | Yu, Xianrui | Zhang, Xueying

Article Type: Research Article

Abstract: Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined …based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications. Show more

Keywords: Emergency plan, case-based reasoning, adaptation, gravitational search algorithm

DOI: 10.3233/JIFS-202132

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11007-11022, 2021

Authors: Alansari, Monairah | Mohammed, Shehu Shagari | 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. 40, no. 6, pp. 11023-11037, 2021

Authors: Nazra, Admi | Asdi, Yudiantri | Wahyuni, Sisri | Ramadhani, Hafizah | Zulvera,

Article Type: Research Article

Abstract: This paper aims to extend the Interval-valued Intuitionistic Hesitant Fuzzy Set to a Generalized Interval-valued Hesitant Intuitionistic Fuzzy Soft Set (GIVHIFSS). Definition of a GIVHIFSS and some of their operations are defined, and some of their properties are studied. In these GIVHIFSSs, the authors have defined complement, null, and absolute. Soft binary operations like operations union, intersection, a subset are also defined. Here is also verified De Morgan’s laws and the algebraic structure of GIVHIFSSs. Finally, by using the comparison table, a different approach to GIVHIFSS based decision-making is presented.

Keywords: Soft sets, intuitionistic fuzzy soft sets, hesitant fuzzy soft sets, interval-valued fuzzy soft sets

DOI: 10.3233/JIFS-202185

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11039-11050, 2021

Authors: Zhang, Yang | Ye, Jianmu

Article Type: Research Article

Abstract: This paper takes the listed pharmaceutical manufacturing firms in China’s A-share market from 2011 to 2017 as the research sample, from the perspective of top managers’ pay gap, employs principal component analysis and general least square method to empirically investigate the effect of risk preference of top management team(TMT) on the re-innovation behavior after the failure of innovation. The study found that the risk preference of TMT is positively correlated with the re-innovation input and brand-new innovation after the failure of innovation, but not with the supplementary innovation. Besides, the pay gap not only has a positive moderating effect on …the positive correlation between the risk preference of TMT and the re-innovation input, but also on the positive correlation between the risk preference of TMT and the brand-new innovation after the failure of innovation. The findings of this study contribute to: (1) through empirical research on the impact of TMT risk preference on re-innovation behavior after innovation failure, expand the relevant research content and research methods of TMT and innovation failure to make the research results more convincing; (2) by setting a reasonable executive compensation gap, TMT can avoid blindly choosing brand-new innovation behavior after innovation failure with the increase of risk preference innovation, ignoring the potential value of innovation failure projects without supplementary innovation, improving the re-innovation behavior of TMT after innovation failure and improving the re innovation success rate after innovation failure. Show more

Keywords: TMT risk preference, re-innovation after the failure, brand-new innovation, supplementary innovation, pay gap

DOI: 10.3233/JIFS-202186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11051-11061, 2021

Authors: Khan, Vakeel A. | Esi, Ayhan | Ahmad, Mobeen | Daud Khan, Mohammad

Article Type: Research Article

Abstract: In this article, we show that the addition and scalar multiplication in neutrosophic normed spaces are continuous. The neutrosophic boundedness and continuity of linear operators between neutrosophic normed spaces are examined. Moreover, we analyzed that the set of all neutrosophic continuous linear operators and the set of all neutrosophic bounded linear operators from neutrosophic normed spaces into another are vector spaces.

Keywords: Bounded linear operator, continuity, neutrosophic normed space

DOI: 10.3233/JIFS-202189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11063-11070, 2021

Authors: Jiang, Chunmao | Guo, Doudou | Sun, Lijuan

Article Type: Research Article

Abstract: The basic idea of the three-way decisions (3WD) is ‘thinking in threes.’ The TAO (trisecting-acting-outcome) model of 3WD includes three components, trisect a whole into three reasonable regions, devise a corresponding strategy on the trisection, and measure the effectiveness of the outcome. By reviewing existing studies, we found that only a few papers touch upon the third component, i.e., measure the effect. This paper’s principal aim is to present an effectiveness measure framework consisting of three parts: a specific TAO model - Change-based TAO model, interval sets, and utility functions with unique characteristics. Specifically, the change-based TAO model provides a …method to measure effectiveness based on the difference before and after applying a strategy or an action. First, we use interval sets to represent these changes when a strategy or an action is applied. These changes correspond to three different intervals. Second, we use the utility measurement method to figure out three change intervals. Namely, different utility measures correspond to the different intervals, concave utility metric, direct utility metric, and convex utility metric, respectively. Third, it aggregates the toll utility through the joint of the three utilities mentioned above. The weights among these three are adjusted by a dual expected utility function that conveys the decision-makers’ preferences. We give an example and experiment highlighting the validity and practicability of the utility measure method in the change-based TAO model of three-way decisions. Show more

Keywords: Three-way decisions, change-based TAO model, interval set, utility measurement, dual expected utility

DOI: 10.3233/JIFS-202207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11071-11084, 2021

Authors: Qian, Tiancheng | Mei, Xue | Xu, Pengxiang | Ge, Kangqi | Qiu, Zhelei

Article Type: Research Article

Abstract: Recently many methods use encoder-decoder framework for video captioning, aiming to translate short videos into natural language. These methods usually use equal interval frame sampling. However, lacking a good efficiency in sampling, it has a high temporal and spatial redundancy, resulting in unnecessary computation cost. In addition, the existing approaches simply splice different visual features on the fully connection layer. Therefore, features cannot be effectively utilized. In order to solve the defects, we proposed filtration network (FN) to select key frames, which is trained by deep reinforcement learning algorithm actor-double-critic. According to behavior psychology, the core idea of actor-double-critic is …that the behavior of agent is determined by both the external environment and the internal personality. It avoids the phenomenon of unclear reward and sparse feedback in training because it gives steady feedback after each action. The key frames are sent to combine codec network (CCN) to generate sentences. The operation of feature combination in CCN make fusion of visual features by complex number representation to make good semantic modeling. Experiments and comparisons with other methods on two datasets (MSVD/MSR-VTT) show that our approach achieves better performance in terms of four metrics, BLEU-4, METEOR, ROUGE-L and CIDEr. Show more

Keywords: Video captioning, deep reinforcement learning, frame sampling, feature fusion, sparse reward, actor-critic

DOI: 10.3233/JIFS-202249

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11085-11097, 2021

Authors: Chen, Yang | Yang, Jiaxiu

Article Type: Research Article

Abstract: In recent years, interval type-2 fuzzy logic systems (IT2 FLSs) have become a hot topic for the capability of coping with uncertainties. Compared with the centroid type-reduction (TR), investigating the center-of-sets (COS) TR of IT2 FLSs is more favorable for applying IT2 FLSs. Actually, it is still an open question for comparing Karnik-Mendel (KM) types of algorithms and other types of alternative algorithms for COS TR. This paper gives the block of fuzzy reasoning, COS TR, and defuzzification of IT2 FLSs based on Nagar-Bardini (NB), Nie-Tan (NT) and Begian-Melek-Mendel (BMM) noniterative algorithms. Six simulation experiments are used to show the …performances of three types of noniterative algorithms. The proposed noniterative algorithms can obtain much higher computational efficiencies compared with the KM algorithms, which give the potential value for designing T2 FLSs. Show more

Keywords: Interval type-2 fuzzy logic systems, center-of-sets type-reduction, Nagar-Bardini algorithms, computational efficiency, Nie-Tan algorithms

DOI: 10.3233/JIFS-202264

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11099-11106, 2021

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. 40, no. 6, pp. 11107-11130, 2021

Authors: Wei, Shanting | Zhang, Zhuo | Chen, Xintong

Article Type: Research Article

Abstract: Network-based incubation has undergone rapid developments and the incubation mechanism has begun to change recently. To incentive the start-ups on the basis of ensuring its own interests, the incubator needs to design a feasible contract. According to network theory, a single network cannot adequately describe the heterogeneous alliances of incubated start-ups in the business incubator. Therefore, by constructing super-network structure of incubated start-ups, this paper designs two types of linear incentive contracts and uses numerical simulation to further discuss the model. The results indicate that the business incubator should design the contract according to the different capability levels and risk …preference degree of start-ups: linear screening contract (LSC) is more effective to motivate the incubated start-ups to improve the capability, while the incentive effect will be weakened by the increasing proportion of high-capability start-ups; for high risk-preference start-ups, linear pooling contract (LPC) is superior than LSC. The results can serve as a theoretical direction for the business incubator to effectively distinguish different capability levels of start-ups and make better decision on contract design to motivate start-ups on the basis of ensuring the maximization of its own utility. Show more

Keywords: Business incubator, start-up, super-network, dynamic capability, cooperative network, knowledge network

DOI: 10.3233/JIFS-202279

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11131-11144, 2021

Authors: Chen, Kuen-Suan | Yu, Chun-Min

Article Type: Research Article

Abstract: Many corporations purchase components from suppliers, which can reduce operating costs and enable firms to focus their resources on core advantages. Studies have indicated that process quality and manufacturing time performance are two crucial indicators for supplier selection. We used the process quality index and a manufacturing time performance index to create a dual dimensional fuzzy supplier selection model. First, the upper confidence limits of these two indices were derived, and a fuzzy membership function based on these limits was constructed. Based on the fuzzy test rules for process quality and manufacturing time performance, we divided the fuzzy supplier selection …matrix into nine evaluation zones. Using the upper confidence limits of these two indices, we created evaluation coordinates and assigned weights based on the location of the coordinates. Then, the total of all the weights was employed to form a supplier selection index for which a higher value means a higher ranking. The use of confidence limits decreased the chance of misjudgment resulting from sampling errors while the fuzzy test rules increased the applicability of the model. Consequently, the proposed model can be used to select suppliers efficiently so as to form partnerships in which corporations and suppliers can grow together. Show more

Keywords: Fuzzy supplier selection model, fuzzy membership function, manufacturing time performance, process quality, upper confidence limit

DOI: 10.3233/JIFS-202349

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11145-11158, 2021

Authors: Lei, Shi

Article Type: Research Article

Abstract: An improved Web community discovery algorithm is proposed in this paper based on the attraction between Web pages to effectively reduce the complexity of Web community discovery. The proposed algorithm treats each Web page in the Web pages collection as an individual with attraction based on the theory of universal gravitation, elaborates the discovery and evolution process of Web community from a Web page in the Web pages collection, defines the priority rules of Web community size and Web page similarity, and gives the calculation formula of the change in Web page similarity. Finally, an experimental platform is built to …analyze the specific discovery process of the Web community in detail, and the changes in cumulative distribution of Web page similarity are discussed. The results show that the change in the similarity of a new page satisfies the power-law distribution, and the similarity of a new page is proportional to the size of Web community that the new page chooses to join. Show more

Keywords: Web community, web page, attraction, evolution process, web page similarity

DOI: 10.3233/JIFS-202366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11159-11169, 2021

Authors: He, Weiming | Wu, You | Xiao, Jing | Cao, Yang

Article Type: Research Article

Abstract: Feature pyramids are commonly applied to solve the scale variation problem for object detection. One of the most representative works of feature pyramid is Feature Pyramid Network (FPN), which is simple and efficient. However, the fully power of multi-scale features might not be completely exploited in FPN due to its design defects. In this paper, we first analyze the structure problems of FPN which prevent the multi-scale feature from being fully exploited, then propose a new feature pyramid structure named Mixed Group FPN (MGFPN) , to mitigate these design defects of FPN. Concretely, MGFPN strengthens the feature utilization by two …modules named Mixed Group Convolution(MGConv) and Contextual Attention(CA) . MGConv reduces the spatial information loss of FPN in feature generation stage. And CA narrows the semantic gaps between features of different receptive field before lateral summation. By replacing FPN with MGFPN in FCOS, our method can improve the performance of detectors in many major backbones by 0.7 to 1.2 Average Precision(AP) on MS-COCO benchmark without adding too much parameters and it is easy to be extended to other FPN-based models. The proposed MGFPN can serve as a simple and strong alternative for many other FPN based models. Show more

Keywords: Object Detection, Feature Pyramids, FPN, Mixed Group Convolution, Contextual Attention

DOI: 10.3233/JIFS-202372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11171-11181, 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. 40, no. 6, pp. 11183-11199, 2021

Authors: Zeng, Shaohua | Wu, Yalan | Wang, Shuai | He, Ping

Article Type: Research Article

Abstract: The segmentation and extraction of the purple soil region from purple soil color image can effectively avoid the influence of background on recognition of soil types. A scale weighted fuzzy c-means clustering algorithm(SWFCM) is proposed for effective segmentation of purple soil color image. The main work is to establish the maximum difference optimization model with the mean of Gaussian distance between each pixel and each peak of the image histogram, and optimize the clustering number and the initial clustering centers. Then, the compactness of each class is defined to weight the Euclidean distance between the pixel and the clustering center …and improve the optimization model of FCM for raising its clustering performance. Aiming at the problem of removing scattered small soil blocks in the background and filling holes in the purple soil region, the algorithm of extracting the boundary of the purple soil region and the algorithm of filling the purple soil region are proposed. Finally, the normal and robust experiments are carried out on the normal sample set and robust sample set. And the performances of relative algorithms are compared, which involves the previously released FCM algorithms and some methods for the segmentation of purple soil color image and our proposed algorithm. Experimental results show that performance of SWFCM is better and it can provide a high reference for adaptive segmentation of purple soil color images. Especially for robust experiment images, its average segmentation accuracy is improved by 6 . 64% ∼ 8 . 25 % compared with other purple soil segmentation algorithms. Show more

Keywords: color image segmentation, purple soil, fuzzy c-means clustering(FCM)

DOI: 10.3233/JIFS-202401

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11201-11215, 2021

Authors: Ghosh, Arijit | Dey, Munmun | Mondal, Sankar Prasad | Shaikh, Azharuddin | Sarkar, Anirban | Chatterjee, Banashree

Article Type: Research Article

Abstract: E-Rickshaw is an E-vehicle that has three wheels, a rechargeable battery driven electric motor as engine. E-rickshaw has become very popular due to low operating cost, low maintenance cost, eco-friendliness and ease of driving. It is perfect for small distance transport. As a last mile connector, it has transformed the public transport system in India. The low cost electric vehicle carries enough people to make a decent income and hence has become a source of livelihood for many. For considering the issues in this paper, detailed attributes of E-rickshaw are studied and Analytical Hierarchy Process (AHP) has been applied to …calculate criteria weights for the sorted attributes. Subsequently, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a Multi Criteria Decision Making (MCDM) technique has been applied for the selection of best E-Rickshaw. In this paper, sensitivity analysis and comparative analysis have been conducted for further insight. Show more

Keywords: AHP method, E-Rickshaws selection, sensitivity analysis, TOPSIS method

DOI: 10.3233/JIFS-202406

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11217-11230, 2021

Authors: Mi, Xiangjun | Tian, Ye | Kang, Bingyi

Article Type: Research Article

Abstract: Describing and processing complex as well as ambiguous and uncertain information has always been an inescapable and challenging topic in multi-attribute decision analysis (MADA) problems. As an extension of Dempster-Shafer (D-S) evidence theory, D numbers breaks through the constraints of the constraint framework and is a new way of expressing uncertainty. The soft likelihood function based on POWA operator is one of the most useful tools recently developed for dealing with uncertain information, since it provides a more excellent performance for the aggregation of multiple compatible evidence. Recently, a new MADA model based on D numbers has been proposed, called …DMADA. In this paper, inspired by the above mentioned theories, based on soft likelihood functions, POWA aggregation and D numbers we design a novel model to improve the performance of representing and processing uncertain information in MADA problems as an improvement of the DMADA approach. In contrast, our advantages include mainly the following. Firstly, the proposed method considers the reliability characteristics of each initial D number information. Secondly, the proposed method empowers decision makers with the possibility to express their perceptions through attitudinal features. In addition, an interesting finding is that the preference parameter in the proposed method can clearly distinguish the variability between candidates by adjusting the space values between adjacent alternatives, making the decision results clearer. Finally, the effectiveness and superiority of this model are proved through analysis and testing. Show more

Keywords: Multi-attribute decision analysis (MADA), D numbers, ordered weighted averaging (OWA), power OWA (POWA), soft likelihood function (SLF), reliability

DOI: 10.3233/JIFS-202413

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11231-11255, 2021

Authors: Pei, Huili | Li, Hongliang | Liu, Yankui

Article Type: Research Article

Abstract: In practical decision-making problems, decision makers are often affected by uncertain parameters because the exact distributions of uncertain parameters are usually difficult to determine. In order to deal with this issue, the major contribution in this paper is to propose a new type of type-2 fuzzy variable called level interval type-2 fuzzy variable from the perspective of level-sets, which is a useful tool in modeling distribution uncertainty. With our level interval type-2 fuzzy variable, we give a method for constructing a parametric level interval (PLI) type-2 fuzzy variable from a nominal possibility distribution by introducing the horizontal perturbation parameters. The …proposed horizontal perturbation around the nominal distribution is different from the vertical perturbation discussed in the literature. In order to facilitate the modeling in practical decision-making problems, for a level interval type-2 fuzzy variable, we define its selection variable whose distribution can be determined via its level-sets. The numerical characteristics like expected value and second order moments are important indices in practical optimization and decision-making problems. With this consideration, we establish the analytical expressions about the expected values and second order moments of the selection variables of PLI type-2 trapezoidal, normal and log-normal fuzzy variables. Furthermore, in order to derive the analytical expressions about the numerical characteristics of the selection variable for the sums of the common PLI type-2 fuzzy variables, we discuss the arithmetic about the sums of common PLI type-2 fuzzy variables. Finally, we apply the proposed optimization method to a pricing decision problem to demonstrate the efficiency of our new method. The computational results show that even a small perturbation of the nominal possibility distribution can affect the quality of solutions. Show more

Keywords: Level interval type-2 fuzzy variable, Selection variable, Second order moments, Pricing decision

DOI: 10.3233/JIFS-202421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11257-11272, 2021

Authors: Wang, Huiru | Zhou, Zhijian

Article Type: Research Article

Abstract: Multi-view learning utilizes information from multiple representations to advance the performance of categorization. Most of the multi-view learning algorithms based on support vector machines seek the separating hyperplanes in different feature spaces, which may be unreasonable in practical application. Besides, most of them are designed to balanced data, which may lead to poor performance. In this work, a novel multi-view learning algorithm based on maximum margin of twin spheres support vector machine (MvMMTSSVM) is introduced. The proposed method follows both maximum margin principle and consensus principle. By following the maximum margin principle, it constructs two homocentric spheres and tries to …maximize the margin between the two spheres for each view separately. To realize the consensus principle, the consistency constraints of two views are introduced in the constraint conditions. Therefore, it not only deals with multi-view class-imbalanced data effectively, but also has fast calculation efficiency. To verify the validity and rationlity of our MvMMTSSVM, we do the experiments on 24 binary datasets. Furthermore, we use Friedman test to verify the effectiveness of MvMMTSSVM. Show more

Keywords: Multi-view learning, twin spheres, SVM, maximum margin, consensus principle

DOI: 10.3233/JIFS-202427

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11273-11286, 2021

Authors: Liu, Peide | Mahmood, Tahir | Ali, Zeeshan

Article Type: Research Article

Abstract: Complex q-rung orthopair fuzzy set (CQROFS) is a proficient technique to describe awkward and complicated information by the truth and falsity grades with a condition that the sum of the q-powers of the real part and imaginary part is in unit interval. Further, Schweizer–Sklar (SS) operations are more flexible to aggregate the information, and the Muirhead mean (MM) operator can examine the interrelationships among the attributes, and it is more proficient and more generalized than many aggregation operators to cope with awkward and inconsistence information in realistic decision issues. The objectives of this manuscript are to explore the SS operators …based on CQROFS and to study their score function, accuracy function, and their relationships. Further, based on these operators, some MM operators based on PFS, called complex q-rung orthopair fuzzy MM (CQROFMM) operator, complex q-rung orthopair fuzzy weighted MM (CQROFWMM) operator, and their special cases are presented. Additionally, the multi-criteria decision making (MCDM) approach is developed by using the explored operators based on CQROFS. Finally, the advantages and comparative analysis are also discussed. Show more

Keywords: Complex q-rung orthopair fuzzy sets, Schweizer-Sklar Muirhead means operators, multi-criteria decision making

DOI: 10.3233/JIFS-202440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11287-11309, 2021

Authors: Xuan, Cho Do | Duong, Duc | Dau, Hoang Xuan

Article Type: Research Article

Abstract: Advanced Persistent Threat (APT) is a dangerous network attack method that is widely used by attackers nowadays. During the APT attack process, attackers often use advanced techniques and tools, thus, causing many difficulties for information security systems. In fact, to detect the APT attacks, intrusion detection systems cannot rely on one technique or method but often combine multiple techniques and methods. In addition, the approach for APT attack detection using behavior analysis and evaluation techniques is facing many difficulties due to the lack of characteristic data of attack campaigns. For the above reasons, in this paper, we propose a method …for APT attack detection based on a multi-layer analysis. The multi-layer analysis technique in our proposal computes and analyzes various events in Network Traffic to detect and synthesize abnormal signs and behaviors in order to make conclusions about the existence of APT in the system. Specifically, in our proposal, we will use serial 3 main layers for the APT attack detection process including i) Detecting APT attacks based on analyzing abnormal connection; ii) Detecting APT attacks based on analyzing and evaluating Suricata log; iii) Detecting APT attacks based on analyzing behavior profiles that are compiled from layers (i) and (ii). To achieve these goals, the multi-layer analysis technique for APT attack detection will perform 2 main tasks: i) Analyzing and evaluating components of Network Traffic based on abnormal signs and behaviors. ii) building and classifying behavior profile based on each component of network traffic. In the experimental section, we will compare and evaluate the effectiveness of the APT attack detection process of each layer in the multi-layer analysis model using machine learning. Experimental results have shown that the APT attack detection method based on analyzing behavior profile has yielded better results than individual detection methods on all metrics. The research results shown in the paper not only demonstrate the effectiveness of the multilayer analysis model for APT attack detection but also provide a novel approach for detecting several other cyber-attack techniques. Show more

Keywords: Advanced persistent threat, APT attack detection, network traffic, multi-layer detection, abnormal behavior, machine learning

DOI: 10.3233/JIFS-202465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11311-11329, 2021

Authors: Revathi, T. | Rajalaxmi, T.M. | Sundara Rajan, R. | Freire, Wilhelm Passarella

Article Type: Research Article

Abstract: Salient object detection plays a vital role in image processing applications like image retrieval, security and surveillance in authentic-time. In recent times, advances in deep neural network gained more attention in the automatic learning system for various computer vision applications. In order to decrement the detection error for efficacious object detection, we proposed a detection classifier to detect the features of the object utilizing a deep neural network called convolutional neural network (CNN) and discrete quaternion Fourier transform (DQFT). Prior to CNN, the image is pre-processed by DQFT in order to handle all the three colors holistically to evade loss …of image information, which in-turn increase the effective use of object detection. The features of the image are learned by training model of CNN, where the CNN process is done in the Fourier domain to quicken the method in productive computational time, and the image is converted to spatial domain before processing the fully connected layer. The proposed model is implemented in the HDA and INRIA benchmark datasets. The outcome shows that convolution in the quaternion Fourier domain expedite the process of evaluation with amended detection rate. The comparative study is done with CNN, discrete Fourier transforms CNN, RNN and masked RNN. Show more

Keywords: Convolutional neural networks, quaternion complex variable, object detection, image enhancement, discrete quaternion Fourier transform

DOI: 10.3233/JIFS-202502

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11331-11340, 2021

Authors: Beseiso, Majdi | Kumar, Gulshan

Article Type: Research Article

Abstract: This paper presents a fuzzy computational approach for selecting project portfolio by combining fuzzy logic, Quality Function Deployment (QFD) and Genetic algorithm (GA) approaches with the consideration of prioritized selection criteria as per objectives of the organization to make decisions effectively with incomplete and ambiguous information to help in portfolio selection. This approach addresses the issues of the uncertainty of experts in selecting projects, prioritizing criteria before initiating project selection process and evaluating the number of interdependent projects for their maximal values. It completes the task in three stages. Firstly, it involves interaction with experts to extract fuzzy input about …the benefits of organization and selection criteria for selecting a project portfolio. The second stage requires the application of fuzzy QFD to prioritize criteria before deciding the project portfolio. In this stage, the paper contributes a method for using fuzzy values in a distinct way for obtaining priorities of selection criteria. The final stage evaluates the candidate projects concurrently based on top priority selection criteria by considering interrelation among projects by proposing a distinct fitness function of GA. The validity of the proposed approach is demonstrated by an example that considers three experts, three objectives of the organization and four selection criteria. Show more

Keywords: Fuzzy quality function development (FQFD), genetic algorithm, project portfolio management, project portfolio selection, quality function development (QFD)

DOI: 10.3233/JIFS-202506

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11341-11354, 2021

Authors: Khan, Vakeel A. | Tuba, Umme | Ashadul Rahaman, SK. | Ahmad, Ayaz

Article Type: Research Article

Abstract: In 1990, Diamond [16 ] primarily established the base of fuzzy star–shaped sets, an extension of fuzzy sets and numerous of its properties. In this paper, we aim to generalize the convergence induced by an ideal defined on natural numbers ℕ , introduce new sequence spaces of fuzzy star–shaped numbers in ℝ n and examine various algebraic and topological properties of the new corresponding spaces as well. In support of our results, we provide several examples of these new resulting sequences.

Keywords: Fuzzy star–shaped numbers, Lp–metric, I–convergence, solidity and convergence free

DOI: 10.3233/JIFS-202534

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11355-11362, 2021

Authors: Aydoğmuş, Hacer Yumurtacı | Kamber, Eren | Kahraman, Cengiz

Article Type: Research Article

Abstract: The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and …Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness. Show more

Keywords: Fuzzy, picture fuzzy sets, CODAS method, ERP selection

DOI: 10.3233/JIFS-202564

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11363-11373, 2021