Journal of Intelligent & Fuzzy Systems - Volume 41, issue 2

Authors: Wu, Meiqin | Hou, Xiaoqing | Fan, Jianping

Article Type: Research Article

Abstract: As an extended model of data envelopment analysis (DEA), cross-efficiency is utilized in various fields. It applies the relative evaluation values of homogeneous decision-making units (DMUs) in ranking completely. Due to the non-uniqueness of DEA optimal weights, and the cross-efficiency methods focus on the aggregation of cross-efficiency matrix values. There is a low correction between the final efficiency evaluation value and the value assigned to the criteria weight or the value of the criteria. This paper uses the modified aggressive cross-efficiency model to calculate the weights of the decision-making units (DMUs). Then according to the consistency of peer-evaluation criteria, the …entropy weight method is used to aggregate the index weights to generate a set of common weights, and a new Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method is used to calculate the utility score of DMUs that can rank them completely. Finally, a numerical case of supplier selection is offered to illustrate the feasibility and effectiveness of the proposed method. Show more

Keywords: Cross-efficiency, group decision-making, criteria utility, MARCOS method

DOI: 10.3233/JIFS-210279

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3107-3119, 2021

Authors: Liu, Donghai | Luo, Yan

Article Type: Research Article

Abstract: Although some correlation measure of intuitionistic fuzzy sets(IFSs) have been proposed, some of them cannot express the consistency of information or satisfy the axioms of similarity measure. In this paper, we present a consensus reaching process based on the concordance correlation measure of IFSs in multi-criteria decision making problems. Firstly, we define an innovative concordance correlation measure of IFSs, which not only takes the average information deviation of IFSs into account but also overcomes the disadvantages of previous correlation measures. In addition, its properties and the relationship between the defined new concordance correlation measure and Pearson correlation coefficient of IFSs …are discussed. Secondly, considering that the classical TOPSIS method cannot be applied to the correlation measure with negative values, we continue to introduce the concept of relative concordance correlation measure and propose a consensus reaching process with minimum adjustment for an innovative behavioral TOPSIS method. Furthermore, a detailed numerical example and the comparison analyses are provided to verify the advantages of the proposed method. At last, we discuss the sensitivity and stability of the method. Show more

Keywords: Concordance correlation measure, Consensus reaching process, Intuitionistic fuzy set, Behavioral TOPSIS

DOI: 10.3233/JIFS-210343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3121-3136, 2021

Authors: Wang, Jinfeng | Huang, Shuaihui | Jiang, Fajian | Zheng, Zhishen | Ou, Jianbin | Chen, Hao | Chen, Runjian | Wang, Wenzhong

Article Type: Research Article

Abstract: Fuzzy integral in data mining is an excellent information fusion tool. It has obvious advantages in solving the combination of features and has more successful applications in classification problems. However, with the increase of the number of features, the time complexity and space complexity of fuzzy integral will also increase exponentially. This problem limits the development of fuzzy integral. This article proposes a high-efficiency fuzzy integral—Parallel and Sparse Frame Based Fuzzy Integral (PSFI) for reducing time complexity and space complexity in the calculation of fuzzy integrals, which is based on the distributed parallel computing framework-Spark combined with the concept of …sparse storage. Aiming at the efficiency problem of the Python language, Cython programming technology is introduced in the meanwhile. Our algorithm is packaged into an algorithm library to realize a more efficient PSFI. The experiments verified the impact of the number of parallel nodes on the performance of the algorithm, test the performance of PSFI in classification, and apply PSFI on regression problems and imbalanced big data classification. The results have shown that PSFI reduces the variable storage space requirements of datasets with aplenty of features by thousands of times with the increase of computing resources. Furthermore, it is proved that PSFI has higher prediction accuracy than the classic fuzzy integral running on a single processor. Show more

Keywords: Parallel computing, sparse storage, fuzzy integral, fuzzy measure

DOI: 10.3233/JIFS-210372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3137-3159, 2021

Authors: Qiu, Liqing | Yang, Zhongqi | Zhu, Shiwei | Gu, Chunmei | Tian, Xiangbo

Article Type: Research Article

Abstract: Influence maximization is a classic network optimization problem, which has been widely used in the field of viral marketing. The influence maximization problem aims to find a fixed number of active nodes. After a specific propagation model, the number of active nodes reaches the maximum. However, the existing influence maximization algorithms are overly pursuing certain indicators of efficiency or accuracy, which cannot be well accepted by some researchers. This paper proposes an effective algorithm to balance the accuracy and efficiency of the influence maximization problem called local two-hop search algorithm (LTHS). The core of the proposed algorithm is a node …not only be affected by one-hop neighbor nodes, but also by two-hop neighbor nodes. Firstly, this paper selects initial seed nodes according to the characteristics of the node degree. Generally, the high degree of nodes regards as influential nodes. Secondly, this paper proposes a node two-hop influence evaluate function called two-hop diffusion value (THDV), which can evaluate node influence more accurately. Furthermore, in order to seek higher efficiency, this paper proposes a method to reduce the network scale. This paper conducted full experiments on five real-world social network datasets, and compared with other four well-known algorithms. The experimental results show that the LTHS algorithm is better than the comparison algorithms in terms of efficiency and accuracy. Show more

Keywords: Social network, influence maximization, local influence, heuristic algorithm

DOI: 10.3233/JIFS-210379

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3161-3172, 2021

Authors: Yiarayong, Pairote

Article Type: Research Article

Abstract: The aim of this manuscript is to apply bipolar fuzzy sets for dealing with several kinds of theories in LA -semigroups. To begin with, we introduce the concept of 2-absorbing (quasi-2-absorbing) bipolar fuzzy ideals and strongly 2-absorbing (quasi-strongly 2-absorbing) bipolar fuzzy ideals in LA -semigroups, and investigate several related properties. In particular, we show that a bipolar fuzzy set A = ( μ A P , μ A N ) over an LA -semigroup S is weakly 2-absorbing …if and only if [ B ⊙ C ] ⊙ D ⪯ A implies B ⊙ C ⪯ A or C ⊙ D ⪯ A or B ⊙ D ⪯ A for any bipolar fuzzy sets B = ( μ B P , μ B N ) , C = ( μ C P , μ C N ) and D = ( μ D P , μ D N ) . Also, we give some characterizations of quasi-strongly 2-absorbing bipolar fuzzy ideals over an LA -semigroup S by bipolar fuzzy points. In conclusion of this paper we prove that the relationship between quasi-strongly 2-absorbing bipolar fuzzy ideals over an LA -semigroup S and quasi-2-absorbing bipolar fuzzy ideals over S . Show more

Keywords: bipolar fuzzy set, 2-absorbing bipolar fuzzy ideal, strongly 2-absorbing bipolar fuzzy ideal, ℒℒ-semigroup, quasi-2-absorbing bipolar fuzzy ideal

DOI: 10.3233/JIFS-210388

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3173-3181, 2021

Authors: Zhao, Shan | Li, Zhao

Article Type: Research Article

Abstract: The interpolation functions of interval type-2 fuzzy systems and their universal approximation are investigated in this paper. Two types of fuzzification methods are designed to construct the antecedents and consequents of the type-2 inference rules. Then the properties of the fuzzy operator and the type-reduction algorithm are used to integrate all parts of the fuzzy system. Interpolation functions of interval type-2 fuzzy systems, which are proved to be universal approximators, are obtained based on three models, namely single input and single output, double inputs and single output, and multiple inputs and single output. The proposed approach is applied to approximate …experiments of dynamic systems so as to evaluate the system performance. The system parameters are optimized by the QPSO algorithm. Experimental results for several data sets are given to show the approximation performances of the proposed interpolation functions are better than those of the interpolation function of the classical type-1 fuzzy system. Show more

Keywords: Interval type-2 fuzzy system, interval type-2 fuzzy set, interpolation function, universal approximation

DOI: 10.3233/JIFS-210435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3183-3200, 2021

Authors: Zixian, Zhang | Xuning, Liu | Zhixiang, Li | Hongqiang, Hu

Article Type: Research Article

Abstract: The influencing factors of coal and gas outburst are complex, and now the accuracy and efficiency of outburst prediction are not high. In order to obtain the effective features from influencing factors and realize the accurate and fast dynamic prediction of coal and gas outburst, this article proposes an outburst prediction model based on the coupling of feature selection and intelligent optimization classifier. Firstly, in view of the redundancy and irrelevance of the influencing factors of coal and gas outburst, we use Boruta feature selection method to obtain the optimal feature subset from influencing factors of coal and gas outburst. …Secondly, based on Apriori association rules mining method, the internal association relationship between coal and gas outburst influencing factors is mined, and the strong association rules existing in the influencing factors and samples that affect the classification of coal and gas outburst are extracted. Finally, svm is used to classify coal and gas outburst based on the above obtained optimal feature subset and sample data, and Bayesian optimization algorithm is used to optimize the kernel parameters of svm, and the coal and gas outburst pattern recognition prediction model is established, which is compared with the existing coal and gas outburst prediction model in literatures. Compared with the method of feature selection and association rules mining alone, the proposed model achieves the highest prediction accuracy of 93% when the feature dimension is 3, which is higher than that of Apriori association rules and Boruta feature selection, and the classification accuracy is significantly improved. However, the feature dimension decreased significantly, the results show that the proposed model is better than other prediction models, which further verifies the accuracy and applicability of the coupling prediction model. Show more

Keywords: Coal and gas outburst, Feature selection, Boruta, Apriori, Bayesian optimization, SVM

DOI: 10.3233/JIFS-210466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3201-3218, 2021

Authors: Yang, Han | Qin, Keyun

Article Type: Research Article

Abstract: The theory of three-way concept analysis has been developed into an effective tool for data analysis and knowledge discovery. In this paper, we propose neutrosophic three-way concept lattice by combining neutrosophic set with three-way concept analysis and present an approach for conflict analysis by using neutrosophic three-way concept lattice. Firstly, we propose the notion of neutrosophic formal context, in which the relationships between objects and attributes are expressed by neutrosophic numbers. Three pairs of concept derivation operators are proposed. The basic properties of object-induced and attribute-induced neutrosophic three-way concept lattices are examined. Secondly, we divide the neutrosophic formal context into …three classical formal contexts and propose the notions of the candidate neutrosophic three-way concepts and the redundant neutrosophic three-way concepts. Two approaches of constructing object-induced (attribute-induced) neutrosophic three-way concept lattices are presented by using candidate, redundant and original neutrosophic three-way concepts respectively. Finally, we apply the neutrosophic formal concept analysis to the conflict analysis and put forward the corresponding optimal strategy and the calculation method of the alliance. Show more

Keywords: Three-way concept analysis, neutrosophic set, neutrosophic three-way concept lattice, conflict analysis

DOI: 10.3233/JIFS-210481

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3219-3236, 2021

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

Article Type: Research Article

Abstract: The optimal supplier selection in medical instrument industries could be considered a classical MAGDM issue. The probabilistic uncertain linguistic term sets (PULTSs) could depict uncertain information well and the Taxonomy method is appropriate to compare various alternatives according to their merits and utility degree from studied attributes. In such paper, we develop a Taxonomy method for probabilistic uncertain linguistic MAGDM (PUL-MAGDM) with the completely unknown attribute weights. Above all, the score function’s definition is utilized to derive the weights of attribute based upon the CRITIC method. In addition, the probabilistic uncertain linguistic development pattern (PULDP) is improved and the smallest …development attribute value from the positive ideal solution under PULTSs is calculated to determine the optimal alternative. In the end, taking the supplier selection in medical instrument industries as an example, we demonstrate the usage of the developed algorithms. Based on this, the comparison of methods is conducted with existing methods, such as PUL-TOPSIS method, the PULWA operator, the PUL-EDAS method and the ULWA operator. The results verify that the decision-making framework is valid and effective for supplier selection. Thus, the advantage of this designed method is that it is simple to understand and easy to compute. The designed method can also contribute to the selection of suitable alternative successfully in other selection issues. Show more

Keywords: Multiple attribute group decision making (MAGDM) issues, probabilistic uncertain linguistic sets (PULTSs), taxonomy approach, CRITIC method, supplier selection

DOI: 10.3233/JIFS-210494

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3237-3250, 2021

Authors: Amsaprabhaa, M. | Nancy Jane, Y. | Khanna Nehemiah, H.

Article Type: Research Article

Abstract: Due to the COVID-19 pandemic, countries across the globe has enforced lockdown restrictions that influence the people’s socio-economic lifecycle. The objective of this paper is to predict the communal emotion of people from different locations during the COVID-19 lockdown. The proposed work aims in developing a deep spatio-temporal analysis framework of geo-tagged tweets to predict the emotions of different topics based on location. An optimized Latent Dirichlet Allocation (LDA) approach is presented for finding the optimal hyper-parameters using grid search. A multi-class emotion classification model is then built via a Recurrent Neural Network (RNN) to predict emotions for each topic …based on locations. The proposed work is experimented with the twitter streaming API dataset. The experimental results prove that the presented LDA model-using grid search along with the RNN model for emotion classification outperforms the other state of art methods with an improved accuracy of 94.6%. Show more

Keywords: Topic modeling, latent dirichlet allocation, grid search, multi-class emotion classification, recurrent neural network

DOI: 10.3233/JIFS-210544

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3251-3264, 2021