Journal of Intelligent & Fuzzy Systems - Volume 41, issue 1

Authors: Sayed, Osama Rashed | Sayed, Nabil Hasan | Chen, Gui-Xiu

Article Type: Research Article

Abstract: In the present paper, a characterization of the intuitionistic fuzzy sets, the interval-valued intuitionistic fuzzy sets and their set-operations are given. By making use of these characterizations, the relationships between the interval-valued intuitionistic fuzzy topology and four fuzzy topologies associated to it are studied. For this reason, some subclasses of the family of interval-valued intuitionistic fuzzy topologies on a set which we call pre-suitable and suitable are introduced. Furthermore, the concepts of homeomorphism functions and compactness in the framework of interval-valued intuitionistic fuzzy topological spaces are introduced and studied.

Keywords: Interval-valued intuitionistic fuzzy set, interval-valued intuitionistic fuzzy topology, fuzzy topology, homeomorphism, compactness

DOI: 10.3233/JIFS-202757

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 879-889, 2021

Authors: Zhang, Qiang | Zhang, Luyu | Sun, Bingzhen

Article Type: Research Article

Abstract: In 2020, the spread of the COVID-19 epidemic has attracted global attention. As a large-scale group that is receiving higher education, college students also show greater mood swings. How to reduce the psychological harm of anxiety to college students is a problem that needs to be solved urgently. Based on this, this paper proposes an evaluation model for the anxiety level of college students in different regions under the influence of COVID-19. First of all, the general influence index of college student’s anxiety level is obtained by correlation analysis. Secondly, the logical OR of the double quantization variable precision fuzzy …set model and the degree fuzzy rough set model is used to establish the evaluation model of the anxiety level of college students under the influence of COVID-19. Finally, used big data, the idea of fuzzy upper and lower approximation, combined with the principle of maximum membership in fuzzy set theory, achieved the quantitative ranking of the anxiety levels of college students in different areas. The research shows that when the accuracy of decision-making is 45%, the anxiety level of the township college students group and the provincial capital or municipality college students group is higher. When the accuracy of decision-making is 65%, the anxiety level of the provincial capital or municipality college students group is higher than others. Show more

Keywords: Fuzzy rough set, two universes, COVID-19, college students anxiety level

DOI: 10.3233/JIFS-202760

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 891-902, 2021

Authors: Aishwarya, N. | BennilaThangammal, C. | Praveena, N.G.

Article Type: Research Article

Abstract: Getting a complete description of scene with all the relevant objects in focus is a hot research area in surveillance, medicine and machine vision applications. In this work, transform based fusion method called as NSCT-FMO, is introduced to integrate the image pairs having different focus features. The NSCT-FMO approach basically contains four steps. Initially, the NSCT is applied on the input images to acquire the approximation and detailed structural information. Then, the approximation sub band coefficients are merged by employing the novel Focus Measure Optimization (FMO) approach. Next, the detailed sub-images are combined using Phase Congruency (PC). Finally, an inverse …NSCT operation is conducted on synthesized sub images to obtain the initial synthesized image. To optimize the initial fused image, an initial decision map is first constructed and morphological post-processing technique is applied to get the final map. With the help of resultant map, the final synthesized output is produced by the selection of focused pixels from input images. Simulation analysis show that the NSCT-FMO approach achieves fair results as compared to traditional MST based methods both in qualitative and quantitative assessments. Show more

Keywords: Image fusion, multi-focus, NSCT, focus measure, decision map

DOI: 10.3233/JIFS-202803

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 903-915, 2021

Authors: Luo, Man

Article Type: Research Article

Abstract: The construction of hydraulic projects inevitably involves land requisition and resettlement, with considerable impact on the society, the environment, and the economy of the project site, and leading to social stability risk events. Therefore, it is necessary to systematically assess social stability risk to put forward corresponding countermeasures. By applying WSR theory (Wuli-Shili-Renli Theory) to the investigation of the case-study of the Jiangxiang Reservoir Project, this paper constructs an evaluation index system for the risk to social stability from land requisition and resettlement, from the three dimensions of “physics”, “matter”, and “human principle”. The GAHP (Group-decision Analytic Hierarchy Process) method …is used to determine the index weights, while the index values of each risk factor are determined by using the interval valued hesitant fuzzy sets (IVHFSs) method. A comprehensive assessment of risks to social stability from land requisition and resettlement in the Jiangxiang Reservoir Project is performed, and coping strategies for major social stability risk factors are proposed. This paper effectively supports the development of assessments of risks to social stability from land requisition and resettlement in other hydraulic projects. Show more

Keywords: Social stability risk assessment, land requisition and resettlement, hydraulic project

DOI: 10.3233/JIFS-202805

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 917-928, 2021

Authors: Mahmood, Nabeel | Qin, Rongjun | Butalia, Tarunjit Singh

Article Type: Research Article

Abstract: A risk assessment model is developed to estimate the potential combined influence of concurrent safety risks facing on-foot construction worker at a certain point in space or instant of time. The model is based on a holistic approach that comprehensively systemizes principal types and subjective values of possible safety risk events. Fuzzy fault tree is built using a deductive approach to identify possible concurrent basic and conditional risk events, not risk symptoms, from the major subgroups of triggering, enabling and environment-related risks. The inclusive risk breakdown structure helps in combating assessment underestimation related to overlooking influential risks. Adequate logic gates …are suggested at tree junctions to overcome assessment overestimation related to accumulating the effect of dependent, redundant, and non-concurrent risks, and ignoring the effectiveness of safety precautions and measures that may reduce or eliminate risks. Operational logic gates are applied to properly combine the residual risk of static (non-moving) events and dynamic (moving) events that can concurrently influence safety. The model is programmed into an interactive interfaced intelligent system to simulate cases of risk assessment input, computations, and output. The system shows the advantages of using the model as a prognostic or diagnostic tool to estimate top risk event. Subjective linguistic risk values can be induced for basic risk events at the bottom of the tree, and conditional risk events controlling residual risk values can be induced at different levels of the tree. Fuzzy logic plays a key role in hosting subjective risk evaluation into computational truth values to generate realistic and meaningful assessment values that are helpful for risk control. Show more

Keywords: On-foot building construction worker, safety risk assessment model, concurrent risk events, static dynamic risks, operational logic gates, fuzzy fault tree analysis, linguistic truth values

DOI: 10.3233/JIFS-202915

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 929-954, 2021

Authors: Riaz, Muhammad | Ali, Nawazish | Davvaz, Bijan | Aslam, Muhammad

Article Type: Research Article

Abstract: The aim of this paper is to introduce the concepts of soft rough q-rung orthopair fuzzy set (SRqROFS) and q-rung orthopair fuzzy soft rough set (qROPFSRS) based on soft rough set and fuzzy soft relation, respectively. We define some fundamental operations on both SRqROFS and qROPFSRS and discuss some key properties of these models by using upper and lower approximation operators. The suggested models are superior than existing soft rough sets, intuitionistic fuzzy soft rough sets and Pythagorean fuzzy soft rough sets. These models are more efficient to deal with vagueness in multi-criteria decision-making (MCDM) problems. We develop Algorithm i …(i  = 1, 2, 3, 4, 5) for the construction of SRqROFS, construction of qROFSRS, selection of a smart phone, ranking of beautiful public parks, and ranking of government challenges, respectively. The notions of upper reduct and lower reduct based on the upper approximations and lower approximations by variation of the decision attributes are also proposed. The applications of the proposed MCDM methods are demonstrated by respective numerical examples. The idea of core is used to find a unanimous optimal decision which is obtained by taking the intersection of all lower reducts and upper reducts. Show more

Keywords: Soft rough q-rung orthopair fuzzy set, q-rung orthopair fuzzy soft rough set, upper reduct, lower reduct, core, multi-criteria decision-making

DOI: 10.3233/JIFS-202916

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 955-973, 2021

Authors: Rath, Adyasha | Patnaik, Srikanta | Panda, Ganapati

Article Type: Research Article

Abstract: The density of population in cities is growing at a faster rate to make the life of people in cities comfortable and save. The city needs to be smart. It can be mainly achieved by intelligent decision making process using computational intelligence based systems. Keeping this in view, many researchers and organizations are working to develop and implement computational intelligence decision support systems. To obtain a comprehensive overview on the current status on SI based smart city community the present investigation has been made. To achieve this objective recently published standard articles on this important sub area have been collected …and reviewed. The summary of the review has been presented in systematic manner to facilitate the researchers who are currently working in the area of smart city community. The important findings of the review have been made and presented. The important performance measures in various aspects of smart city obtained by the computational intelligence methods have been listed. It is expected that the findings and the contribution of the paper will benefit the researchers, the related government and private organizations in terms of furthering their research efforts and producing different smart products pertaining to community development and improvement of comfort level of the dwellers of the smart city. Show more

Keywords: Smart city, computational intelligence, machine learning, intelligent transportation system, smart healthcare, smart environment, smart education, cyber security

DOI: 10.3233/JIFS-202919

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 975-991, 2021

Authors: Priyadharshini, V.M. | Valarmathi, A.

Article Type: Research Article

Abstract: Online social networks (OSNs) are utilized by millions of people from the entire world to communicate with others through Facebook and Twitter. The removal of fake accounts will increase the efficiency of the protection in OSNs. The construction of the OSN model has the nodes and the links to identify the fake profiles on Twitter. This paper proposes a novel technique to detect spam profiles and the proposed classifier is to classify the profile images from the dataset. The malicious profile detection technique is used to identify the fake profiles with the concept of a Twitter crawler that implements the …extraction of data from the profile. The feature set analysis has been implemented with the feature related analysis. The user behavior detection utilizes the adjacent matrix to measure the similarity values within the friend’s profiles. The multi-variant Support Vector Machine classifier is developed for efficient classification with the kernel function. The proposed technique is compared with the well-known techniques of ECRModel, ISMA and DeepLink that the detection rate is 2.5% higher than the related techniques, the computation time is 220 s lesser than the related techniques and the proposed technique has 3.1% higher accuracy. Show more

Keywords: Online social networks, twitter, spam detection, classification, malicious node

DOI: 10.3233/JIFS-202937

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 993-1007, 2021

Authors: Zhang, Huiyuan | Wei, Guiwu | Chen, Xudong

Article Type: Research Article

Abstract: The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes …through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified. Show more

Keywords: Multiple attribute group decision making (MAGDM), spherical fuzzy sets (SFSs), MABAC method, cumulative prospect theory (CPT), entropy method, combined weights, green supplier selection

DOI: 10.3233/JIFS-202954

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1009-1019, 2021

Authors: Demirci, Işıl Açık | Gürdal, Mehmet

Article Type: Research Article

Abstract: In this work, we study the lacunary I -statistical convergence concept of complex uncertain triple sequence. Four types of lacunary I -statistically convergent complex uncertain triple sequences are presented, namely lacunary I -statistical convergence in measure, in mean, in distribution and with respect to almost surely, and some basic properties are proved.

Keywords: Triple sequence, statistical convergence, ideal convergence, triple lacunary sequence, complex uncertain variable, uncertainty space

DOI: 10.3233/JIFS-202964

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1021-1029, 2021

Authors: Wu, Qiongling | Lin, Jian | Zhang, Shaohan | Tian, Zhiyong

Article Type: Research Article

Abstract: This paper constructs the continuous-Young optimal weighted arithmetic averaging (C-YOWA) operator and the continuous-Young optimal weighted geometric (C-YOWG) operator based on definite integral and Young inequality. A series of special cases and main properties of the proposed aggregation operators are also investigated. In order to integrate heterogeneous interval data and obtain more accurate prediction results, the heterogeneous interval combination prediction (HICP) model based on C-YOWA operator, C-YOWG operator and Theil coefficient is proposed. The HICP model consider not only the existence of both additive and multiplicative interval information, but also the preference information of experts. Finally, the model is applied …to the empirical analysis of wind energy prediction. The comparison of results shows that the established model can effectively improve the accuracy of prediction. Show more

Keywords: Combination prediction, continuous aggregation operator, interval number, young inequality, Theil coefficient

DOI: 10.3233/JIFS-210004

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1031-1048, 2021

Authors: Dong, Yuanxiang | Deng, Xinglu | Hu, Xinyu | Chen, Weijie

Article Type: Research Article

Abstract: Suppliers can be regarded as unavoidable sources of external risks in modern supply chains, which may cause disruption of supply chains. A resilient supplier usually has a high adaptive ability to reduce the vulnerability against disruptions and recover from disruption to keep continuity in operations. This paper develops an effective multi-attribute group decision-making (MAGDM) framework for resilient supplier selection. Because of the many uncertainties in resilient supplier selection, the dual hesitant fuzzy soft sets (DHFSSs), a very flexible tool to express uncertain and complex information of decision-makers, is utilized to cope with it. In order to obtain the resilient supplier’s …partial order relationship and consider the psychological behavior of decision-makers, this paper proposes the MAGDM framework with DHFSSs based on the TOPSIS method and prospect theory for resilient supplier selection. Furthermore, we consider the consensus level among experts of different backgrounds and experiences and propose a consensus measure method based dual hesitant fuzzy soft numbers (DHFSNs) before selecting a resilient supplier. The expert weights are calculated by the group consensus level between the expert and the group opinions. Meanwhile, we define the entropy of DHFSSs to determine the attribute weights objectively in the decision-making process. Based on this, the proposed method is applied to a practical manufacturing enterprise with an international supply chain for a resilient supplier selection problem. Finally, by performing a sensitivity analysis and a comparative analysis, the results demonstrate the robustness and validity of the proposed method. Show more

Keywords: Resilient supplier selection, group decision making, dual hesitant fuzz soft sets, consensus measure, entropy

DOI: 10.3233/JIFS-210025

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1049-1067, 2021

Authors: Liao, Wei | Wei, Xiaohui | Lai, Jizhou

Article Type: Research Article

Abstract: A novel actor-critic algorithm is introduced and applied to zero-sum differential game. The proposed novel structure consists of two actors and a critic. Different actors represent the control policies of different players, and the critic is used to approximate the state-action utility function. Instead of neural network, the fuzzy inference system is applied as approximators for the actors and critic so that the specific practical meaning can be represented by the linguistic fuzzy rules. Since the goals of the players in the game are completely opposite, the actors for different players are simultaneously updated in opposite directions during the training. …One actor is updated updated toward the direction that can minimize the Q value while the other updated toward the direction that can maximize the Q value. A pursuit-evasion problem with two pursuers and one evader is taken as an example to illustrate the validity of our method. In this problem, the two pursuers the same actor and the symmetry in the problem is used to improve the replay buffer. At the end of this paper, some confrontations between the policies with different training episodes are conducted. Show more

Keywords: Fuzzy inference system, differential game, reinforcement learning, pursuit-evasion problem, deterministic policy gradient

DOI: 10.3233/JIFS-210032

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1069-1082, 2021

Authors: Priyadarshi, Ankur | Saha, Sujan Kumar

Article Type: Research Article

Abstract: In this paper, we present our effort on the development of a Maithili Named Entity Recognition (NER) system. Maithili is one of the official languages of India, with around 50 million native speakers. Although various NER systems have been developed in several Indian languages, we did not find any openly available NER resource or system in Maithili. For the development, we manually annotated a Maithili NER corpus containing around 200K words. We prepared a baseline classifier using Conditional Random Fields (CRF). Then we ran many experiments using various recurrent neural networks (RNN). We collected larger raw corpus to obtain better …word embedding and character embedding. In our experiments, we found, neural models are better than CRF; a CRF layer is effective for the prediction of the final output in the RNN models; character embedding is effective in Maithili language. We also investigated the effectiveness of gazetteer lists in neural models. We prepared a few gazetteer lists from various web resources and used those in the neural models. The incorporation of the gazetteer layer caused performance improvement. The final system achieved an f-measure of 91.6% with 94.9% precision and 88.53% recall. Show more

Keywords: Named entity recognition, Maithili language, corpus annotation, LSTM model, gazetteer lists

DOI: 10.3233/JIFS-210051

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1083-1095, 2021

Authors: Rehman, Hafiz Asadul | Zafar, Kashif | Khan, Ayesha | Imtiaz, Abdullah

Article Type: Research Article

Abstract: Discovering structural, functional and evolutionary information in biological sequences have been considered as a core research area in Bioinformatics. Multiple Sequence Alignment (MSA) tries to align all sequences in a given query set to provide us ease in annotation of new sequences. Traditional methods to find the optimal alignment are computationally expensive in real time. This research presents an enhanced version of Bird Swarm Algorithm (BSA), based on bio inspired optimization. Enhanced Bird Swarm Align Algorithm (EBSAA) is proposed for multiple sequence alignment problem to determine the optimal alignment among different sequences. Twenty-one different datasets have been used in order …to compare performance of EBSAA with Genetic Algorithm (GA) and Particle Swarm Align Algorithm (PSAA). The proposed technique results in better alignment as compared to GA and PSAA in most of the cases. Show more

Keywords: Multiple sequence alignment, Particle swarm optimization, Bioinformatics, Genetic algorithm, swarm intelligence, bird swarm algorithm

DOI: 10.3233/JIFS-210055

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1097-1114, 2021

Authors: Zhou, Ze-Nan | Zhou, Zhiheng | Huang, Junchu

Article Type: Research Article

Abstract: Patch-based deep convolutional neural network (DCNN) has been proved to have advanced performance in no-reference image quality assessment (NR-IQA). However, these methods generally take global quality score as the quality score of each patch mainly since local quality score is not provided. Unfortunately, the perceived quality of image patch is difficult to maintain a high degree of consistency. Thus, the use of the same global quality score in different patches of the same image may hinder training of DCNNs. In this paper, we propose a universal and nearly cost-free model called Gaussian Random Jitter (GRJ). According to the uncertainty of …the perceived quality, GRJ divided the training images into high-confidence distorted images and low-confidence distorted images, and reasonably assigned different local quality scores to each patch through specific gaussian functions with the global quality score as the mean value and the undetermined hyperparameter as the standard deviation. We took one of the most advanced patch-based DCNNs models as backbone and tested the improved performance over three widely used image quality databases. We show that our model can further improve the performance of patch-based models and even help them comparable with those of state-of-the-art NR-IQA algorithms. Show more

Keywords: Patch, gaussian distribution, convolutional neural networks, no-reference image quality assessment

DOI: 10.3233/JIFS-210063

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1115-1124, 2021

Authors: Imran, Muhammad | Ali, Yasir | Malik, Mehar Ali | Hasnat, Kiran

Article Type: Research Article

Abstract: Chromatic spectrum of a colored graph G is a multiset of eigenvalues of colored adjacency matrix of G . The nullity of a disconnected graph is equal to sum of nullities of its components but we show that this result does not hold for colored graphs. In this paper, we investigate the chromatic spectrum of three different classes of 2-regular bipartite colored graphs. In these classes of graphs, it is proved that the nullity of G is not sum of nullities of components of G . We also highlight some important properties and conjectures to extend this problem …to general graphs. Show more

Keywords: Spectrum of graph, nullity of graph, graph coloring

DOI: 10.3233/JIFS-210066

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1125-1133, 2021

Authors: Liu, Haitao | Zhang, Qiang

Article Type: Research Article

Abstract: This paper studies cooperative games in which players have multiple attributes. Such games are applicable to situations in which each player has a finite number of independent additive attributes in cooperative games and the payoffs of coalitions are endogenous functions of these attributes. The additive attributes cooperative game, which is a special case of the multiattribute cooperative game, is studied with respect to the core, the conditions for existence and boundedness and methods of transformation regarding a general cooperative game. A coalitional polynomial form is also proposed to discuss the structure of coalition. Moreover, a Shapley-like solution called the efficient …resource (ER) solution for additive attributes cooperative games is studied via the axiomatical method, and the ER solution of two additive attribute games with equivalent total resources coincides with the Shapley value. Finally, some examples of additive attribute games are given. Show more

Keywords: Multiple attributes, cooperative games, Shapley value, core, solution

DOI: 10.3233/JIFS-210088

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1135-1150, 2021

Authors: Zulqarnain, Rana Muhammad | Xin, Xiao Long | Garg, Harish | Ali, Rifaqat

Article Type: Research Article

Abstract: In this article, we investigate the multi-criteria decision-making complications under Pythagorean fuzzy soft information. The Pythagorean fuzzy soft set (PFSS) is a proper extension of the Pythagorean fuzzy set (PFS) which discusses the parametrization of the attributes of alternatives. It is also a generalization of the intuitionistic fuzzy soft set (IFSS). The PFSS is used to precisely evaluate the deficiencies, anxiety, and hesitation in decision-making (DM). The most essential determination of the current study is to advance some operational laws along with aggregation operators (AOs) within the Pythagorean fuzzy soft environs such as Pythagorean fuzzy soft interaction weighted average (PFSIWA) …and Pythagorean fuzzy soft interaction weighted geometric (PFSIWG) operators with their desirable features. Furthermore, a DM technique has been established based on the developed operators to solve multi-criteria decision-making (MCDM) problems. Moreover, an application of the projected method is presented for the selection of an effective hand sanitizer during the COVID-19 pandemic. A comparative analysis with the merits, effectivity, tractability, along with some available research deduces the effectiveness of this approach. Show more

Keywords: Pythagorean fuzzy sets, Pythagorean fuzzy soft sets, PFSIWA operator, PFSIWG operator, hand sanitizer

DOI: 10.3233/JIFS-210098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1151-1171, 2021

Authors: Lina, Wang | Zeshui, Xu

Article Type: Research Article

Abstract: Risk management is a significant part of the success of a public-private partnership (PPP) project. There are four phrases for the process of risk management: Constructing a risk management environment, identifying risk factors, evaluating risk factors, and allocating risk factors. After identifying risk factors, it is imperative to analyze and evaluate critical risk factors, which can help participants formulate strategies to allocate risk factors, and thus alleviate the possible adverse results. The objectives of analyzing and evaluating risk factors focus on two aspects: The possibilities of risk occurrence and the degrees of risk loss. On behalf of determining the critical …risk factors effectively, we take the probability degree and linguistic expressions into consideration to manifest experts’ perspectives. We consider critical risk factors in terms of the probabilistic linguistic terms with weakened hedges from the evidential reasoning approach view. The linguistic terms with weakened hedges are applied to express the degree of risk risk loss, and the possibilities of risk occurrence collect from the probabilities of linguistic terms with weakened hedges. First, the commonality function and plausibility function are applied to correct the possibilities of risk occurrence for linguistic terms with weakened hedges. Next, we build a risk evaluation model from experts’ risk propensity and risk perceptions. Moreover, a case study of the risk analyzing and evaluating process of a PPP project is applied to illustrate the availability and effectiveness of the proposed model. We contrast the introduced model with other approaches. Finally, the advantages of this model intend to improve the linguistic terms with weakened hedges for the probabilistic linguistic terms with weakened hedges and evaluate risk factors considering the evidence reasoning approach. Show more

Keywords: Risk evaluation, Probabilistic linguistic terms with weakened hedges, Evidential reasoning theory, Public-private partnership project

DOI: 10.3233/JIFS-210101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1173-1191, 2021

Authors: Zhao, Yifan | Tian, Shuicheng

Article Type: Research Article

Abstract: Aiming at the problem of large error and long time of early warning response in the traditional system, this paper designs a hazard identification early warning system based on random forest algorithm in underground coal mine. By random classification decision forest created dangerous content in different areas of the downhole information input into the decision tree as a test sample, according to the result of the output of the leaf node determine the risk level of decision trees, and USES the high precision of decision forest classification ability the threat level assessment test sample, radically reducing hazards identification error. Then, …based on the evaluation results, combined with the threshold value of warning criteria to identify the gas exceeding limit area, and determine the fire source warning level, so as to realize the hazard source identification and warning. The simulation results show that the average hazard location identification error of the system is only 4.1%, and the warning response time can be controlled within 9 s. Show more

Keywords: Underground hazard sources, identify early warning, random forest algorithm, decision forest, risk assessment, alarm criteria threshold

DOI: 10.3233/JIFS-210105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1193-1202, 2021

Authors: Kavitha, N | Ruba Soundar, K | Sathis Kumar, T

Article Type: Research Article

Abstract: In recent years, the Face recognition task has been an active research area in computer vision and biometrics. Many feature extraction and classification algorithms are proposed to perform face recognition. However, the former usually suffer from the wide variations in face images, while the latter usually discard the local facial features, which are proven to be important for face recognition. In this paper, a novel framework based on merging the advantages of the Key points Local Binary/Tetra Pattern (KP-LTrP) and Improved Hough Transform (IHT) with the Improved DragonFly Algorithm-Kernel Ensemble Learning Machine (IDFA-KELM) is proposed to address the face recognition …problem in unconstrained conditions. Initially, the face images are collected from the publicly available dataset. Then noises in the input image are removed by performing preprocessing using Adaptive Kuwahara filter (AKF). After preprocessing, the face from the preprocessed image is detected using the Tree-Structured Part Model (TSPM) structure. Then, features, such as KP-LTrP, and IHT are extracted from the detected face and the extracted feature is reduced using the Information gain based Kernel Principal Component Analysis (IG-KPCA) algorithm. Then, finally, these reduced features are inputted to IDFA-KELM for performing FR. The outcomes of the proposed method are examined and contrasted with the other existing techniques to confirm that the proposed IDFA-KELM detects human faces efficiently from the input images. Show more

Keywords: Face recognition, kernel ensemble learning machine, adaptive kuwahara filter, improved dragonfly algorithm

DOI: 10.3233/JIFS-210130

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1203-1216, 2021

Authors: Li, Lulu

Article Type: Research Article

Abstract: Set-valued data is a significant kind of data, such as data obtained from different search engines, market data, patients’ symptoms and behaviours. An information system (IS) based on incomplete set-valued data is called an incomplete set-valued information system (ISVIS), which generalized model of a single-valued incomplete information system. This paper gives feature selection for an ISVIS by means of uncertainty measurement. Firstly, the similarity degree between two information values on a given feature of an ISVIS is proposed. Then, the tolerance relation on the object set with respect to a given feature subset in an ISVIS is obtained. Next, λ …-reduction in an ISVIS is presented. What’s more, connections between the proposed feature selection and uncertainty measurement are exhibited. Lastly, feature selection algorithms based on λ -discernibility matrix, λ -information granulation, λ -information entropy and λ -significance in an ISVIS are provided. In order to better prove the practical significance of the provided algorithms, a numerical experiment is carried out, and experiment results show the number of features and average size of features by each feature selection algorithm. Show more

Keywords: Rough set theory, ISVIS, feature selection, similarity degree, λ-reduction, λ-discernibility matrix, λ-information granulation, λ-information entropy, λ-significance, algorithm

DOI: 10.3233/JIFS-210135

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1217-1235, 2021

Authors: Wang, Lu

Article Type: Research Article

Abstract: With the prosperity of national economy and the development of highway construction, highway freight transportation plays an increasingly important role in the market economy. Due to its great flexible characteristic, highway freight transportation has been the main mode of transportation in China. On the macro level, there are many factors affecting the development of highway freight transportation especially under the background of the new era. Based on the historical data of the development of highway freight transportation, grey entropy analysis method is applied to analyze the significance of influencing factors for the development of highway freight transportation whose key indicator …is highway freight turnover. Then GM (1, N) model is established to predict the development trend of highway freight turnover and its significant influencing factors. Finally, main problems existing in highway freight transportation and development prospect were discussed and analyzed. The research results show that the three most significant factors affecting the development of road freight turnover in China are the total state revenue, GDP and average distance of highway freight. The established GM (1, N) model can conduct high precision prediction for the development of highway freight transportation. Opportunities and challenges of highway freight transportation industry coexist and its development prospect is promising. It is expected to provide beneficial references for the development strategy and decision-making of highway freight transportation in China. Show more

Keywords: Highway freight transportation, significance analysis, grey entropy analysis method, GM (1, N) prediction model

DOI: 10.3233/JIFS-210141

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1237-1246, 2021

Authors: Tao, Ning | Xiaodong, Duan | Lu, An | Tao, Gou

Article Type: Research Article

Abstract: A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and …company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified. Show more

Keywords: Flexible job-shop scheduling, deteriorating effect, emergency order insertion, disruption management, multi-phase quantum particle swarm optimization

DOI: 10.3233/JIFS-210166

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1247-1259, 2021

Authors: Bahrami, Vahid | Kalhor, Ahmad | Masouleh, Mehdi Tale

Article Type: Research Article

Abstract: This study intends to investigate the dynamic model estimation and the design of an adaptive neural network based controller for a passive planar robot, performing 2-DoF motion pattern which is in interaction with an actuated cable-driven robot. In fact, the main goal of applying this structure is to use a number of light cables to drive serial robot links and track the desired reference model by the robot’s end-effector. The under study system can be used as a rehabilitation setup which is helpful for those with arm disability. In this way, upon applying sliding mode error dynamics, it is necessary …to determine a vector that contains the matrices related to the robot dynamics. However, finding these matrices requires the use of computational approaches such as Newton-Euler or Lagrange. In addition, since the purpose of this paper is to express comprehensive methods, so with increasing the number of links and degrees of freedom of the robot, finding the dynamics of the robot becomes more difficult. Therefore, the Adaptive Neural Network (ANN) with specific inputs has been used for estimation unknown matrices of the system and the controller design has been performed based on it. So, the main idea in using an adaptive controller is the fact there is no pre-knowledge for the dynamic modeling of the system since the human arm could have different dynamic properties. Hence, the controller is formed by an ANN and robust term. In this way, the adaptation laws of the parameters are extracted by Lyapunov approach, and as a result, as aforementioned, the asymptotic stability of the whole of the system is guaranteed. Simulation results certify the efficiency of the proposed method. Finally, using the Roots Mean Square Error (RMSE) criteria, it has been revealed that, in the presence of bounded disturbance with different amplitude, adding the robust term to the controller leads to improve the tracking error about 34% and 62%, respectively. Show more

Keywords: Dynamic model estimation, adaptive neural network controller, lyapunov approach, passive planar robot, actuated cable-driven robot and rehabilitation setup

DOI: 10.3233/JIFS-210180

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1261-1280, 2021

Authors: Wenbo Huang, First A. | Changyuan Wang, Second B. | Hongbo Jia, Third C.

Article Type: Research Article

Abstract: Traditional intention inference methods rely solely on EEG, eye movement or tactile feedback, and the recognition rate is low. To improve the accuracy of a pilot’s intention recognition, a human-computer interaction intention inference method is proposed in this paper with the fusion of EEG, eye movement and tactile feedback. Firstly, EEG signals are collected near the frontal lobe of the human brain to extract features, which includes eight channels, i.e., AF7, F7, FT7, T7, AF8, F8, FT8, and T8. Secondly, the signal datas are preprocessed by baseline removal, normalization, and least-squares noise reduction. Thirdly, the support vector machine (SVM) is …applied to carry out multiple binary classifications of the eye movement direction. Finally, the 8-direction recognition of the eye movement direction is realized through data fusion. Experimental results have shown that the accuracy of classification with the proposed method can reach 75.77%, 76.7%, 83.38%, 83.64%, 60.49%,60.93%, 66.03% and 64.49%, respectively. Compared with traditional methods, the classification accuracy and the realization process of the proposed algorithm are higher and simpler. The feasibility and effectiveness of EEG signals are further verified to identify eye movement directions for intention recognition. Show more

Keywords: EM, EEG, tactile feedback, wireless sensor network, flying driving, brain electrical signals, data fusion

DOI: 10.3233/JIFS-210191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1281-1296, 2021

Authors: Narendiranath Babu, T. | Senthilnathan, N. | Pancholi, Shailesh | Nikhil Kumar, S.P. | Rama Prabha, D. | Mohammed, Noor | Wahab, Razia Sultana

Article Type: Research Article

Abstract: This study aims at developing a novel method for condition monitoring technique for detection and classification of developing faults and increase the working life of continuous variable transmission (CVT) using Daubechies Wavelet 06 (DB-06). The vibration data is collected for 4 different types of faults and healthy condition. Using a magnetic accelerometer and signal analyser, vibration data is collected from the system in the time-domain which is then used as input for a MATLAB code producing the plot of the frequency-domain signal. Maximum frequency is determined to diagnose the faults which are induced over three different belts. Collected data for …large scale automotive system (CVT) is used to train the network and then it is tested based on random data points. Faults were classified using ANN with a classification rate of 90.8 %. Show more

Keywords: Continuous variable transmission (CVT), Daubechies wavelet, fault diagnosis, fault classification, artificial neural network

DOI: 10.3233/JIFS-210199

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1297-1307, 2021

Authors: Guo, Wang | Liu, Xingmou | Ma, You | Zhang, Rongjie

Article Type: Research Article

Abstract: The correct identification of gene recombination cold/hot spots is of great significance for studying meiotic recombination and genetic evolution. However, most of the existing recombination spots recognition methods ignore the global sequence information hidden in the DNA sequence, resulting in their low recognition accuracy. A computational predictor called iRSpot-DCC was proposed in this paper to improve the accuracy of cold/hot spots identification. In this approach, we propose a feature extraction method based on dinucleotide correlation coefficients that focus more on extracting potential DNA global sequence information. Then, 234 representative features vectors are filtered by SVM weight calculation. Finally, a convolutional …neural network with better performance than SVM is selected as a classifier. The experimental results of 5-fold cross-validation test on two standard benchmark datasets showed that the prediction accuracy of our recognition method reached 95.11%, and the Mathew correlation coefficient (MCC) reaches 90.04%, outperforming most other methods. Therefore, iRspot-DCC is a high-precision cold/hot spots identification method for gene recombination, which effectively extracts potential global sequence information from DNA sequences. Show more

Keywords: Recombination spots, correlation coefficient, DNA property matrix, support vector machines, convolutional neural network

DOI: 10.3233/JIFS-210213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1309-1317, 2021

Authors: Shahzadi, Sundas | Rasool, Areen | Sarwar, Musavarah | Akram, Muhammad

Article Type: Research Article

Abstract: Bipolarity plays a key role in different domains such as technology, social networking and biological sciences for illustrating real-world phenomenon using bipolar fuzzy models. In this article, novel concepts of bipolar fuzzy competition hypergraphs are introduced and discuss the application of the proposed model. The main contribution is to illustrate different methods for the construction of bipolar fuzzy competition hypergraphs and their variants. Authors study various new concepts including bipolar fuzzy row hypergraphs, bipolar fuzzy column hypergraphs, bipolar fuzzy k -competition hypergraphs, bipolar fuzzy neighborhood hypergraphs and strong hyperedges. Besides, we develop some relations between bipolar fuzzy k …-competition hypergraphs and bipolar fuzzy neighborhood hypergraphs. Moreover, authors design an algorithm to compute the strength of competition among companies in business market. A comparative analysis of the proposed model is discuss with the existing models such bipolar fuzzy competition graphs and fuzzy competition hypergraphs. Show more

Keywords: Bipolar fuzzy competition hypergraphs, bipolar fuzzy k-competition hypergraphs, bipolar fuzzy neighborhood hypergraphs

DOI: 10.3233/JIFS-210216

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1319-1339, 2021

Authors: Nandal, Amita | Blagojevic, Marija | Milosevic, Danijela | Dhaka, Arvind | Mishra, Lakshmi Narayan

Article Type: Research Article

Abstract: This paper proposes a deep learning framework for Covid-19 detection by using chest X-ray images. The proposed method first enhances the image by using fuzzy logic which improvises the pixel intensity and suppresses background noise. This improvement enhances the X-ray image quality which is generally not performed in conventional methods. The pre-processing image enhancement is achieved by modeling the fuzzy membership function in terms of intensity and noise threshold. After this enhancement we use a block based method which divides the image into smooth and detailed regions which forms a feature set for feature extraction. After feature extraction we insert …a hashing layer after fully connected layer in the neural network. This hash layer is advantageous in terms of improving the overall accuracy by computing the feature distances effectively. We have used a regularization parameter which minimizes the feature distance between similar samples and maximizes the feature distance between dissimilar samples. Finally, classification is done for detection of Covid-19 infection. The simulation results present a comparison of proposed model with existing methods in terms of some well-known performance indices. Various performance metrics have been analysed such as Overall Accuracy, F-measure, specificity, sensitivity and kappa statistics with values 93.53%, 93.23%, 92.74%, 92.02% and 88.70% respectively for 20:80 training to testing sample ratios; 93.84%, 93.53%, 93.04%, 92.33%, and 91.01% respectively for 50:50 training to testing sample ratios; 95.68%, 95.37%, 94.87%, 94.14%, and 90.74% respectively for 80:20 training to testing sample ratios have been obtained using proposed method and it is observed that the results using proposed method are promising as compared to the conventional methods. Show more

Keywords: Covid-19, deep learning, eucledian distance, fuzzy logic, negative likelihood, hashing and machine learning

DOI: 10.3233/JIFS-210222

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1341-1351, 2021

Authors: Yang, Lehua | Li, Dongmei | Tan, Ruipu

Article Type: Research Article

Abstract: Solving the shortest path problem is very difficult in situations such as emergency rescue after a typhoon: road-damage caused by a typhoon causes the weight of the rescue path to be uncertain and impossible to represent using single, precise numbers. In such uncertain environments, neutrosophic numbers can express the edge distance more effectively: membership in a neutrosophic set has different degrees of truth, indeterminacy, and falsity. This paper proposes a shortest path solution method for interval-valued neutrosophic graphs using the particle swarm optimization algorithm. Furthermore, by comparing the proposed algorithm with the Dijkstra, Bellman, and ant colony algorithms, potential shortcomings …and advantages of the proposed method are deeply explored, and its effectiveness is verified. Sensitivity analysis performed using a 2020 typhoon as a case study is presented, as well as an investigation on the efficiency of the algorithm under different parameter settings to determine the most reasonable settings. Particle swarm optimization is a promising method for dealing with neutrosophic graphs and thus with uncertain real-world situations. Show more

Keywords: Interval-valued neutrosophic numbers, neutrosophic graph, particle swarm optimization algorithm, shortest path problem

DOI: 10.3233/JIFS-210233

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1353-1373, 2021

Authors: Yu, Xiaobing | Liu, Zhenjie | Wu, XueJing | Wang, Xuming

Article Type: Research Article

Abstract: Differential evolution (DE) is one of the most effective ways to solve global optimization problems. However, considering the traditional DE has lower search efficiency and easily traps into local optimum, a novel DE variant named hybrid DE and simulated annealing (SA) algorithm for global optimization (HDESA) is proposed in this paper. This algorithm introduces the concept of “ranking” into the mutation operation of DE and adds the idea of SA to the selection operation. The former is to improve the exploitation ability and increase the search efficiency, and the latter is to enhance the exploration ability and prevent the algorithm …from trapping into the local optimal state. Therefore, a better balance can be achieved. The experimental results and analysis have shown its better or at least equivalent performance on the exploitation and exploration capability for a set of 24 benchmark functions. It is simple but efficient. Show more

Keywords: Differential evolution, simulated annealing, ranking, mutation operator, selection operator

DOI: 10.3233/JIFS-210239

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1375-1391, 2021

Authors: Al-shami, Tareq M. | Alshammari, Ibtesam | El-Shafei, Mohammed E.

Article Type: Research Article

Abstract: In 1982, Pawlak proposed the concept of rough sets as a novel mathematical tool to address the issues of vagueness and uncertain knowledge. Topological concepts and results are close to the concepts and results in rough set theory; therefore, some researchers have investigated topological aspects and their applications in rough set theory. In this discussion, we study further properties of N j -neighborhoods; especially, those are related to a topological space. Then, we define new kinds of approximation spaces and establish main properties. Finally, we make some comparisons of the approximations and accuracy measures introduced herein and their counterparts …induced from interior and closure topological operators and E -neighborhoods. Show more

Keywords: Nj-neighborhoods, Ej-neighborhoods, j-neighborhood space, lower and upper approximations, accuracy measure, topological space

DOI: 10.3233/JIFS-210272

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1393-1406, 2021

Authors: Nguyen, Huyen Trang | Chu, Ta-Chung

Article Type: Research Article

Abstract: Understanding employees’ perceptions in team collaboration may help managers select and develop effective teamwork and efficient job completion. Numerous criteria, including qualitative and quantitative, and their importance weights must be considered in evaluating individual diversity perception; therefore, evaluating individual diversity perception is a fuzzy multiple criteria decision-making (MCDM) problem. The purpose of this paper is to use a fuzzy MCDM method to evaluate the personal perception of working in a diverse workgroup. A ranking method using the mean of relative values is proposed to rank the final fuzzy values to complete the model. Formulas of the ranking procedure are derived …to help execute the decision-making procedure and a numerical comparison is conducted to demonstrate the advantage of the proposed ranking method. In addition, a survey about personal diversity perception and willingness to work verifies the feasibility and validity of the proposed mean of relative values based fuzzy MCDM method. The results indicate that decision-makers prefer to work in a different countries-same working field group. More experienced decision-makers, unlike students, prefer to work in the same working sector group. Show more

Keywords: Individual diversity perception, fuzzy MCDM, ranking method, mean of relative values

DOI: 10.3233/JIFS-210291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1407-1428, 2021

Authors: He, Yan | Wei, Guiwu | Chen, Xudong | Wei, Yu

Article Type: Research Article

Abstract: The financial products selection in the financial services sector is a traditional multi-attribute group decision making (MAGDM) problem. Probabilistic uncertain linguistic sets (PULTSs) could be used to evaluate the financial products with uncertain linguistic terms and corresponding weights (probabilistic). The bidirectional projection (BP) method could take the bidirectional projection values into account. In this paper, we develop an integration model of information entropy and BP method under PULTSs. First of all, utilizing information entropy derives the priority weights of attributes. Next, utilizing the BP method of the PULTSs to obtain the final ranking of the alternatives. To depict the BP …method, the formative vectors of two alternatives are defined, and a weighted vector model and inner product are improved under the PULTSs. In addition, through giving the case of financial products selection and some existing MAGDM methods for comparative analysis, it is proved that the method is practical and effective. The proposed approach also contributes to the effective selection of appropriate options in other decision-making matters. Show more

Keywords: Multi-attribute group decision making (MAGDM), probabilistic uncertain linguistic sets (PULTSs), bidirectional projection (BP) method, information entropy, financial products selection

DOI: 10.3233/JIFS-210313

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1429-1443, 2021

Authors: Botsa, Devaki Rani | Peddi, Phani Bushan Rao | Boddu, Vikas

Article Type: Research Article

Abstract: This paper proposes a new method to rank the parametric form of fuzzy numbers based on defuzzification. The defuzzification process use centroids, value, ambiguity and decision levels on fuzzy number developed from the parametric form of a generalized fuzzy number. The proposed method avoids reducing function to remove lower alpha levels and can overcome the shortcomings in some of the existing fuzzy ranking methods. The proposed method can effectively rank symmetric fuzzy numbers with the same core and different heights, fuzzy numbers with the same support and different cores, crisp numbers, crisp numbers having the same support and different heights, …and fuzzy numbers having compensation of areas. A demonstration of the proposed method through examples and a comparative study with other methods in the literature shows that the proposed method gives effective results. Show more

Keywords: Fuzzy numbers, ranking, value, ambiguity, centroids, decision level

DOI: 10.3233/JIFS-210327

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1445-1459, 2021

Authors: Wang, Lei | Peng, Xindong

Article Type: Research Article

Abstract: It is prominent important for managers to assess the personal risk of mental patients. The evaluation process refers to numerous indexes, and the evaluation values are general portrayed by uncertainty information. In order to conveniently model the complicated uncertainty information in realistic decision making, interval-valued complex Pythagorean fuzzy set is proposed. Firstly, with the aid of Einstein t-norm and t-conorm, four fundamental operations for interval-valued complex Pythagorean fuzzy number (IVCPFN) are constructed along with some operational properties. Subsequently, according to these proposed operations, the weighted average and weighted geometric forms of aggregation operators are initiated for fusing IVCPFNs, and their …anticipated properties are also examined. In addition, a multiple attribute decision making issue is examined under the framework of IVCPFNs when employing the novel suggested operators. Ultimately, an example regarding the assessment on personal risk of mental patients is provided to reveal the practicability of the designed approach, and the attractiveness of our results is further found through comparing with other extant approaches.The main novelty of the coined approach is that it not only can preserve the original assessment information adequately by utilizing the IVCPFNs, but also can aggregate IVCPFNs effectively. Show more

Keywords: Multiple attribute decision making, Einstein operation, interval-valued complex Pythagorean fuzzy number, aggregation operators, personal risk

DOI: 10.3233/JIFS-210352

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1461-1486, 2021

Authors: Tang, Bin | Guo, Shiwei | Yeboah, Mathias | Wang, Zhenhua | Cheng, Song

Article Type: Research Article

Abstract: After sudden outbreak of COVID-19 pandemic, the university campuses were closed and millions of university teachers and students had to shift teaching and learning activities from the classrooms to online courses in China. The COVID-19 pandemic undoubtedly brought significant negative effects to university education activities. How does COVID-19 influenced teaching quality and the degree of influences have been studied by many researches. However, the online course quality which is influences by COVID-19 pandemic was commonly evaluated qualitatively rather than quantitatively. In order to obtain quantitative evaluation results of online course quality during the pandemic period, the integrated FCE-AHP evaluation was …applied. Based on real case of online courses, the influence factors of online course quality were divided into four first-level indicators and further subdivided into 14 second level indicators. The weight vectors of evaluation indicators were determined based on experts’ comments from the Teaching Affairs Committee and the fuzzy evaluation memberships were calculated based on questionnaire results of 2021 students. The evaluation results revealed that the integral performance of online courses is acceptable and the performances of students and hardware are relative weaker. Finally, some improvement measures were conducted to deal with difficulties encountered in online courses during COVID-19 pandemic period. Show more

Keywords: Fuzzy comprehensive evaluation, analytic hierarchy process, COVID-19, online courses, quantitative evaluation

DOI: 10.3233/JIFS-210362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1487-1498, 2021

Authors: Wang, Qian

Article Type: Research Article

Abstract: With the rapid development of China’s economic globalization in the new era, the demand for English majors is obviously on the rise, which puts forward new and higher requirements for application-oriented undergraduate colleges to train compound English majors. However, from the perspective of teaching quality evaluation of English majors in application-oriented undergraduate colleges, the results are not optimistic. Therefore, it is an important task for higher education research in China to explore the problems existing in the process of teaching quality evaluation for English majors in application-oriented undergraduate colleges and how to better train qualified and versatile talents for English …majors to adapt to the economic and social development in the new era. The teaching quality evaluation of college English is frequently viewed as a multi-attribute group decision-making (MAGDM). Thus, a novel MAGDM method is used to tackle it. Depending on the conventional CODAS method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel distance based IVIF-CODAS method to assess the teaching quality evaluation of college English. First of all, a related literature review is conducted. What’s more, some necessary theories related to IVIFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IVIFSs, the conventional CODAS method is extended to the IVIFSs to calculate assessment score of every alternative. Therefore, all alternatives can be ranked and the one with the best teaching quality. Eventually, an application about teaching quality evaluation of college English and some comparative methods have been employed to show the superiority of the developed method. The results illustrate that the defined framework is very useful for assessing the teaching quality of college English. Show more

Keywords: MAGDM issues, interval-valued intuitionistic fuzzy sets (IVIFSs), CODAS method, CRITIC method, teaching quality, college English

DOI: 10.3233/JIFS-210366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1499-1508, 2021

Authors: Yue, Xiaofeng | Ma, Guoyuan | Liu, Fuqiuxuan | Gao, Xueliang

Article Type: Research Article

Abstract: Due to the complexity and variety of textures on Strip steel, it is very difficult to detect defects on rigid surfaces. This paper proposes a metal surface defect classification method based on an improved bat algorithm to optimize BP neural network. First, this paper uses the Local Binary Pattern(LBP) algorithm to extract features from six types of defect images including inclusion, patches, crazing, pitted, rolled-in, and scratches, and build a feature sample library with the extracted feature values. Then, the WG-BA-BP network is used to classify the defect images with different characteristics. The weighted experience factor added by the network …can control the flight speed of the bat according to the number of iterations and the change of the fitness function. And the gamma distribution is added in the process of calculating loudness, which enhances the local searchability. The BP network optimized by this method has higher accuracy. Finally, to verify the effectiveness of the method, this article introduces the five evaluation indicators of accuracy, precision, sensitivity, specificity, and F1 value under the multi-class model. To prove that this algorithm is more feasible and effective compared with other swarm intelligence algorithms. The best prediction performance of WG-BA-BP is 0.010905, and the accuracy rate can reach 0.9737. Show more

Keywords: Image classification, BP neural network, Bat Algorithm, weighted experience factor, Gamma distribution

DOI: 10.3233/JIFS-210374

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1509-1521, 2021

Authors: Aslam, Muhammad | Albassam, Mohammed

Article Type: Research Article

Abstract: In this paper, tests of skewness and kurtosis are introduced under neutrosophic statistics. The necessary measures and neutrosophic forms of these estimators are introduced. The application of the proposed tests is given using the data associated with heart diseases. From the real example analysis, the proposed tests are quite flexible and informative than the existing tests under classical statistics. In addition, it is concluded from the analysis that the proposed tests give information about the measure of indeterminacy in the presence of uncertainty.

Keywords: Skewness, kurtosis, normality, Neutrosophy, heart disease

DOI: 10.3233/JIFS-210375

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1523-1529, 2021

Authors: Li, Baolin | Yang, Lihua

Article Type: Research Article

Abstract: Picture fuzzy set (PFS) and linguistic term set (LTS) are two significant notions in multi-criteria decision-making (MCDM). In practice, decision-makers sometimes need utilize the multiple probable membership degrees for an uncertain linguistic term to express evaluation information. Motivated by these, to better convey the vagueness and uncertainty of cognitive information, multi-valued picture fuzzy uncertain linguistic set combining picture hesitant fuzzy set with uncertain linguistic term set is proposed. We firstly define the concepts of multi-valued picture fuzzy uncertain linguistic set and multi-valued picture fuzzy uncertain linguistic number. Hamacher operations are more general and flexible in information fusion, thus, Hamacher operations …and comparison method are developed at the same time. Improved generalized Heronian Mean operator can simultaneously reflect correlations between values and prevent the redundant calculation. Then, two operators of improved generalized weighted Heronian mean and improved generalized geometric weighted Heronian mean in view of Hamacher operations are proposed. Meanwhile, some distinguished properties and instances of two operators are explored as well. Moreover, a novel MCDM approach applying the developed operators is constructed. Ultimately, an illustrative example on vendor selection is performed, and sensitivity analysis and comparison analysis are provided to verify the powerfulness of the proposed method. Show more

Keywords: Hamacher, improved generalized heronian operator, multi-criteria decision-making, multi-valued picture fuzzy uncertain linguistic set

DOI: 10.3233/JIFS-210404

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1531-1552, 2021

Authors: Akram, Muhammad | Siddique, Saba | Ahmad, Uzma

Article Type: Research Article

Abstract: The main objective of this research article is to classify different types of m -polar fuzzy edges in an m -polar fuzzy graph by using the strength of connectedness between pairs of vertices. The identification of types of m -polar fuzzy edges, including α -strong m -polar fuzzy edges, β -strong m -polar fuzzy edges and δ -weak m -polar fuzzy edges proved to be very useful to completely determine the basic structure of m -polar fuzzy graph. We analyze types of m -polar fuzzy edges in strongest m -polar fuzzy path and m -polar fuzzy cycle. Further, we define …various terms, including m -polar fuzzy cut-vertex, m -polar fuzzy bridge, strength reducing set of vertices and strength reducing set of edges. We highlight the difference between edge disjoint m -polar fuzzy path and internally disjoint m -polar fuzzy path from one vertex to another vertex in an m -polar fuzzy graph. We define strong size of an m -polar fuzzy graph. We then present the most celebrated result due to Karl Menger for m -polar fuzzy graphs and illustrate the vertex version of Menger’s theorem to find out the strongest m -polar fuzzy paths between affected and non-affected cities of a country due to an earthquake. Moreover, we discuss an application of types of m -polar fuzzy edges to determine traffic-accidental zones in a road network. Finally, a comparative analysis of our research work with existing techniques is presented to prove its applicability and effectiveness. Show more

Keywords: α-strong m-polar fuzzy edges, β-strong m-polar fuzzy edges, Menger’s theorem for m-polar fuzzy graphs, Traffic-accidental zones in a road network, Flowchart

DOI: 10.3233/JIFS-210411

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1553-1574, 2021

Authors: Vaiyapuri, Thavavel | Alaskar, Haya | Sbai, Zohra | Devi, Shri

Article Type: Research Article

Abstract: Medical images that are acquired with reduced radiation exposure or following the administration of imaging agents with a low dose, are often known to experience problems by the noise stemming from acquisition hardware as well as psychological sources. This noise can adversely affect the quality of diagnosis, but also prevent practitioners from computing quantitative functional information. With a view to overcoming these challenges, the current paper puts forward optimization of multi-objective for denoising medical images within the wavelet domain. This proposed technique entails the use of genetic algorithm (GA) to get the threshold optimized within the denoising framework of wavelets. …Two purposes are associated with this technique: First, its ability to adapt with different noise types of noise in the image without requiring prior information about the imaging process per se. In addition, it balances relevant diagnostic details’ preservation against the reduction of noise by considering the optimization of the error factor of Liu and SNR as the foundation of objective function. According to the implementation of this method on magnetic resonance (MR) and ultrasound (US) images of the brain, a better performance has been observed as compared to the existing wavelet-based denoising methods with regard to quantitative and qualitative metrics. Show more

Keywords: Medical image denoising, rician noise, speckle noise, wavelet thresholding, threshold optimization, optimization techniques, multi-objective optimization

DOI: 10.3233/JIFS-210429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1575-1588, 2021

Authors: Yin, Fangchen | Ji, Qinzhi | Jin, Chengwei | Wang, Jing

Article Type: Research Article

Abstract: Milling force prediction is one of the most important ways to improve the quality of products and stability in robot stone machining. In this paper, support vector machines (SVMs) are introduced to model the milling force of white marble, and the model parameters in the SVMs are optimized by the improved quantum-behaved particle swarm optimization (IQPSO) algorithm. A set of online inspection data from stone-machining robotic manipulators is adopted to train and test the model. The overall performance of the model is evaluated based on the decision coefficient (R2), mean absolute percentage error (MAPE) and root mean square error (RMSE), …and the results obtained by IQPSO-SVM are superior to those of the PSO-SVM model. On this basis, the relationship between the milling force of white marble and various machining parameters is explored to obtain optimal machining parameters. The proposed model provides a tool for the adjustment of machining parameters to ensure stable machining quality. This approach is a new method and concept for milling force control and optimization research in the robotic stone milling process. Show more

Keywords: Robot stone machining, quantum-behaved particle swarm algorithm, regression of support vector machines, milling force of white marble, machining parameters

DOI: 10.3233/JIFS-210430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1589-1609, 2021

Authors: Dang, Xingyue | Liao, Shan | Cheng, Pengsen | Liu, Jiayong

Article Type: Research Article

Abstract: Recently, deep learning methods have been applied to deal with the opinion target extraction (OTE) task with fruitful achievements. On the other hand, since the features captured by the embedding layer can make a multiple-perspective analysis from a sentence, an embedding layer that can grasp the high-level semantics of the sentences is of essence for processing the OTE task and can improve the performance of model into a more efficient manner. However, most of the existing studies focused on the network structure rather than the significant embedded layer, which may be the fundamental reason for the problem of relatively poor …performance in this field, not mention the Chinese extraction model. To compensate these shortcomings, this paper proposes a model using multiple effective features and Bidirectional Encoder Representations from Transformers (BERT) on the architecture of Bidirectional Long Short-Term Memory (BiLSTM) and Conditional Random Field (CRF) for Chinese opinion target extraction task, namely MF-COTE, which can construct features from different perspectives to capture the context and local features of the sentences. Besides, to handle the difficult case of multiple nouns in one sentence, we innovatively propose noting words feature to regulate the model emphasize on the noun near the transition or contrast word, thus leading a better opinion target location. Moreover, to demonstrate the superiorities of the proposed model, extensive comparison experiments are systematically conducted compared with other existing state-of-the-art methods, with the F1-score of 90.76%, 92.10%, 89.63% on the Baidu, the Dianping, and the Mafengwo dataset, respectively. Show more

Keywords: Chinese opinion target extraction, multiple features, noting words, BERT, Long short-term memory

DOI: 10.3233/JIFS-210440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1611-1626, 2021

Authors: Garg, Harish | Ali, Zeeshan | Yang, Zaoli | Mahmood, Tahir | Aljahdali, Sultan

Article Type: Research Article

Abstract: The paper aims to present a concept of a Complex interval-valued q-rung orthopair uncertain linguistic set (CIVQROULS) and investigated their properties. In the presented set, the membership grades are considered in terms of the interval numbers under the complex domain while the linguistic features are added to address the uncertainties in the data. To further discuss more, we have presented the operation laws and score function for CIVQROULS. In addition to them, we present some averaging and geometric operators to aggregate the different pairs of the CIVQROULS. Some fundamental properties of the proposed operators are stated. Afterward, an algorithm for …solving the decision-making problems is addressed based on the proposed operator using the CIVQROULS features. The applicability of the algorithm is demonstrated through a case study related to brain tumors and their effectiveness is compared with the existing studies. Show more

Keywords: Aggregation operators, classifications of brain tumors, complex interval valued; q-rung orthopair uncertain linguistic sets

DOI: 10.3233/JIFS-210442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1627-1656, 2021

Authors: Rodriguez, Luis | Castillo, Oscar | Garcia, Mario | Soria, Jose

Article Type: Research Article

Abstract: The main goal of this paper is to outline a new optimization algorithm based on String Theory, which is a relative new area of physics. The String Theory Algorithm (STA) is a nature-inspired meta-heuristic, which is based on studies about a theory stating that all the elemental particles that exist in the universe are strings, and the vibrations of these strings create all particles existing today. The newly proposed algorithm uses equations based on the laws of physics that are stated in String Theory. The main contribution in this proposed method is the new techniques that are devised in order …to generate potential solutions in optimization problems, and we are presenting a detailed explanation and the equations involved in the new algorithm in order to solve optimization problems. In this case, we evaluate this new proposed meta-heuristic with three cases. The first case is of 13 traditional benchmark mathematical functions and a comparison with three different meta-heuristics is presented. The three algorithms are: Flower Pollination Algorithm (FPA), Firefly Algorithm (FA) and Grey Wolf Optimizer (GWO). The second case is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting a statistical comparison of these results with respect to FA and GWO. In addition, we are presenting a third case, which is the optimization of a fuzzy inference system (FIS), specifically finding the optimal design of a fuzzy controller, where the main goal is to optimize the membership functions of the FIS. It is important to mention that we used these study cases in order to analyze the proposed meta-heuristic with: basic problems, complex problems and control problems. Finally, we present the performance, results and conclusions of the new proposed meta-heuristic. Show more

Keywords: New algorithm, stochastic process, performance, string theory, metaheuristics, control problem

DOI: 10.3233/JIFS-210459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1657-1675, 2021

Authors: Saeed, Muhammad | Ahsan, Muhammad | Ur Rahman, Atiqe | Saeed, Muhammad Haris | Mehmood, Asad

Article Type: Research Article

Abstract: Brain tumors are one of the leading causes of death around the globe. More than 10 million people fall prey to it every year. This paper aims to characterize the discussions related to the diagnosis of tumors with their related problems. After examining the side effects of tumors, it encases similar indications, and it is hard to distinguish the precise type of tumors with their seriousness. Since in practical assessment, the indeterminacy and falsity parts are frequently dismissed, and because of this issue, it is hard to notice the precision in the patient’s progress history and cannot foresee the period …of treatment. The Neutrosophic Hypersoft set (NHS) and the NHS mapping with its inverse mapping has been design to overcome this issue since it can deal with the parametric values of such disease in more detail considering the sub-parametric values; and their order and arrangement. These ideas are capable and essential to analyze the issue properly by interfacing it with scientific modeling. This investigation builds up a connection between symptoms and medicines, which diminishes the difficulty of the narrative. A table depending on a fuzzy interval between [0, 1] for the sorts of tumors is constructed. The calculation depends on NHS mapping to adequately recognize the disease and choose the best medication for each patient’s relating sickness. Finally, the generalized NHS mapping is presented, which will encourage a specialist to extricate the patient’s progress history and to foresee the time of treatment till the infection is relieved. Show more

Keywords: Tumor, neutrosophic hypersoft, mapping, inverse mapping

DOI: 10.3233/JIFS-210482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1677-1699, 2021