Journal of Intelligent & Fuzzy Systems - Volume 45, issue 2

Authors: Zhao, Jie | Wan, Renxia | Miao, Duoqian

Article Type: Research Article

Abstract: Multi-granulation decision-theoretic rough set effectively combines Bayesian decision approaches with multi-granulation rough set theory, and provides an important theoretical framework for studying rough set. In this paper, we explore several extensional models of multi-granulation decision-theoretic rough sets under the normal distribution of the decision loss function. Using the 3σ rule of normal distribution, we transform the decision loss of the multi-granulation decision-theoretic rough set into a set of interval values. We construct the upper and lower approximations from the optimistic, weakly optimistic, pessimistic, weakly pessimistic, optimistic-pessimistic, weakly optimistic-pessimistic, pessimistic-optimistic, and weakly pessimistic-optimistic viewpoints, and provide the decision rules of the …proposed rough set models. The work in this paper brings the decision behavior based on a multi-granulation decision-theoretic rough set closer to the actual situation. Show more

Keywords: Loss function, normal distribution, interval value, multi-granulation decision-theoretic rough set

DOI: 10.3233/JIFS-224538

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2031-2046, 2023

Authors: Ma, Mingxi | Wang, Jinliang

Article Type: Research Article

Abstract: The point features of low-texture images are insufficient and unreliable, so it is difficult to achieve good alignment and easy to damage the image structure. To solve these problems, in this paper, we propose a new image stitching method by using the sigmoid function to create perception mask. Firstly, the point features and line features are used to improve the accuracy of image registration and the naturalness of distortion. Secondly, an energy function is used to optimize the alignment model. Finally, we propose to use sigmoid function to create perception mask image to reduce artifacts and retain image structure. The …gradient domain fusion algorithm is combined to achieve image fusion. Experimental results are provided to demonstrate that the proposed method is superior to some previous methods in reducing artifacts and maintaining image structure. Show more

Keywords: Image stitching, sigmoid function, perception mask, gradient domain fusion algorithm, double features

DOI: 10.3233/JIFS-230006

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2047-2061, 2023

Authors: Qu, Liangdong | Li, Xiaoqin | Tan, Mindong | Jia, Yingjuan

Article Type: Research Article

Abstract:  Reducing the dimensions of the original data set while preserving the information as much as possible is conducive to improving the accuracy and efficiency of the model. To achieve this, this paper presents a multi-strategy African vulture optimization algorithm that is the chaotic and elite opposition-based African vulture optimization with the simplex method and differential evolution strategy(CESDAVO). Three main improvements are introduced into African vultures optimization(AVO) to improve its capabilities in this study. Firstly, the chaotic elite opposition-based learning strategy is used to initialize and diversify individual positions of vultures. Secondly, the simplex method is used to optimize those poor …individuals so as to further improve the local exploitation ability of the algorithm. Thirdly, the differential evolution strategy is used to make the algorithm escape from the local optimum and improve the global optimization capability of the algorithm. The results of the ablation experiments show that mixing the three strategies greatly improves the optimization performance of the algorithm. In addition, Nine algorithms are compared with CESDAVO on 15 benchmark functions, and this experimental result shows that its optimization capability is superior to the others. Then, the proposed CESDAVO is employed for feature selection, and 12 standard datasets are used for experiments. According to the experimental results, CESDAVO obtained the highest average classification accuracy on 11 datasets and the highest feature selection rate on 8 datasets, which is significantly better than other algorithms. Finally, CESDAVO is also applied to feature reduction for essays, removing 24 features and significantly improving the classification accuracy on multiple classifiers. Show more

Keywords: Multi-strategy African vulture optimization algorithm, feature selection, essay scoring

DOI: 10.3233/JIFS-230421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2063-2082, 2023

Authors: Zhao, Hua | Li, Xiaoqian | Wang, Fengling | Zeng, Qingtian | Diao, Xiuli

Article Type: Research Article

Abstract:  As one of the fundamental tasks in natural language processing, Multi-Label Text Classification (MLTC) is used to mark one or more relevant labels for a given text from a large set of labels. Existing MLTC methods have increasingly focused on improving classification effectiveness by fusing the correlations of labels. Still, the research suffers from difficulties in comprehensively extracting text features and distinguishing similar labels. This paper proposed a multi-label text classification model based on keyword extraction and attention mechanism. The model proposed using keywords to represent labels, adopting both self-attention and interactive attention mechanisms (between labels and text) to extract …text features and create text vectors. Finally, fusing text vectors as the classifier’s input. Experiments were conducted on two public datasets and a self-built dataset of illegal advertisements. The experimental results showed that the keyword-based label representation approach proposed in this paper can better obtain label semantics, avoid noise and improve the performance of the multi-label text classification. Show more

Keywords: Multi-label text classification, keyword extraction, attention mechanism, label indicates, natural language processing

DOI: 10.3233/JIFS-230506

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2083-2093, 2023

Authors: Ma, Mingxi | Yang, Junci

Article Type: Research Article

Abstract: Many recent studies have shown that Euler’s elastica regularization performs better than the famous total variation (TV) regularization on keeping image features in smooth regions during the process of denoising. In addition, an adaptive weighted matrix combined with total variation is a key technique for well restoring local features of image. Considering these two factors, in this paper, we propose an adaptive Euler’s elastica model for Poisson image restoration so as to well preserve both image features in smooth regions and local features of image. To solve this non-smooth and non-convex model efficiently, we design an alternating direction method of …multipliers. Experiments on both natural and synthetic images illustrate the effectiveness and efficiency of the proposed method over the state-of-the-art methods in Poisson restoration and denoising, respectively. In particular, for Poisson restoration, our proposed method improves the TV method up to 2.46 about PSNR for dealing with the Peppers image with Gaussian blur and noise level σ = 1. In addition, the proposed method for Poisson denoising gets higher PSNR and SSIM values than the TAC method, while costing less CPU time. Show more

Keywords: Poisson restoration, Euler’s elastica regularization, adaptive weighted matrix, alternating direction method of multipliers (ADMM)

DOI: 10.3233/JIFS-230562

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2095-2110, 2023

Authors: Khamis, Adela | Ahmad, Abd Ghafur

Article Type: Research Article

Abstract: This paper presents the concepts of a complex intuitionistic fuzzy subfield (CIFSF) and the direct product of a complex intuitionistic fuzzy subfield which is generalized from the concept of a complex fuzzy subfield by adding the notion of intuitionistic fuzzy into a complex fuzzy subfield. The main contribution and originality of this research are adding the non-membership term to the definition of a complex fuzzy subfield that assigns for any element a complex-valued grade. We expand the complex fuzzy subfield and obtain a new structure called CIFSF. This new concept is innovative in that it may attain a wider range …of values for both membership and non-membership functions where these functions are expanded to the unit disc in the complex plane. Furthermore, we discuss that the direct product of two CIFSFs is CIFSF, and some related properties are investigated. In addition, we present the definition of necessity and possibility operators on the direct product of CIFSF, and some associated theorems are given. Finally, we propose the level subsets of the direct product of two complex intuitionistic fuzzy subsets of a field and prove that the level subset of the direct product of two CIFSFs is a subfield and discuss some related results. Show more

Keywords: Fuzzy sets, intuitionistic fuzzy sets, direct product of complex intuitionistic fuzzy sets, complex fuzzy subfield, complex intuitionistic fuzzy subfield, direct product of complex intuitionistic fuzzy subfield

DOI: 10.3233/JIFS-230597

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2111-2132, 2023

Authors: Zhao, Jiangtao | Sheng, Yuhong

Article Type: Research Article

Abstract: Support vector machine (SVM) is a supervised binary classifier with good generalization ability and excellent computational properties. It has been widely used in many fields such as image recognition, bioinformatics and so on. However, the traditional SVM requires the input data to be clear and knowable, while in the actual application process, there will be many cases that the input data is uncertain. In order to solve this problem, a new SVM model is proposed in this paper by combining the uncertainty theory with the SVM theory. The uncertainty theory was proposed by Liu in 2007, and it is often …used to describe the uncertainty of things. The uncertain set in uncertainty theory is often used to model unsharp concepts. Therefore, this paper regards each uncertain data as an uncertain set and establishes a SVM model with uncertain chance constraints. However, the uncertain chance constraints are non-convex. Therefore, this paper gives the equivalent transformation process of constraint conditions when the input data are triangular uncertain sets. Finally, the non-convex constraint conditions are transformed into the linear constraint conditions, so that the model is transformed into a nonlinear programming model. In the numerical experiment, the Particle Swarm Optimization (PSO) algorithm is used to solve the problem, which proves the feasibility of the model. Show more

Keywords: Support vector machine, uncertainty theory, uncertain set, uncertain support vector machine

DOI: 10.3233/JIFS-230935

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2133-2144, 2023

Authors: Zhang, Qian | Wang, Jianguo

Article Type: Research Article

Abstract: Association rule algorithm has always been a research hotspot in the field of data mining, in the context of today’s big data era, in order to efficiently obtain association rules and effectively update them, based on the original fast update pruning (FUP) algorithm, an association rule incremental update algorithm (FBSCM) based on sorting compression matrix is proposed to solve the shortcomings of frequent scanning of transaction datasets. Firstly, The algorithm maps the transaction dataset as a Boolean matrix, and changes the storage mode of the matrix(that is, adding two columns and a row vector); Secondly, the matrix is compressed many …times during the generation of frequent k- itemset; After that, the items in the matrix are sorted incrementally according to the support degree of the itemset; Finally, the original string comparison operation is replaced by the vector product of each column of the matrix. Experimental results and analysis show that the FBSCM algorithm has higher temporal performance than the traditional FUP algorithm in different incremental dataset sizes, different minimum support thresholds and different feature datasets, especially when the incremental transaction volume is large or the minimum support degree is small. Show more

Keywords: FUP algorithm, boolean matrix, matrix compression, incremental association rule mining

DOI: 10.3233/JIFS-231252

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2145-2156, 2023

Authors: Zhang, Hao | Sheng, Yuhong

Article Type: Research Article

Abstract: Regression analysis is a potent tool to explore the relationship of variables and widely used in many areas. Classical statistics assume that the residual of regression model should follow the Gauss-Markov hypothesis. However, in many cases, the data is not obeying this hypothesis particularly real-life data. Therefore, this paper explores the Von Bertalanffy regression model under the framework of the uncertainty theory, and employs the uncertain maximum likelihood estimation (MLE) to estimate the unknown parameters. Furthermore, the uncertain hypothesis test and an algorithm for data modification which aimed to find outliers and modify data are studied, then the forecast value …and confidence interval be formulated. Finally, a real-life numerical example of applying the above theories be given, this example shows that the uncertain MLE has better performance compare with the uncertain least squares and the least absolute deviations methods. Consequently, the uncertain MLE is a better way to deal with the real-life data. Show more

Keywords: Regression analysis, uncertain Von Bertalanffy regression model, uncertain maximum likelihood estimation, real-life data

DOI: 10.3233/JIFS-231512

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2157-2165, 2023

Authors: Li, Rui

Article Type: Research Article

Abstract: In the current era of economic and cultural globalization, the demand for packaging design is increasing, and the packaging design requirements for brands and products in the entire consumer market are becoming increasingly strict and refined. Designers are facing one greater challenge after another. Packaging design, as a comprehensive discipline that integrates commerce, culture, and art, diverse cultural forms and elements will run through the entire process of brand packaging design. Good products need to be sold through good channels in order to achieve greater value. As a bridge connecting products and the market, the role of packaging design is …even more evident. It can not only improve the recognition of products, but also help enterprises stand out among many similar products, thereby increasing product value. The brand packaging design effect evaluation is a classical multiple attribute group decision making (MAGDM) problem. This paper extends the EDAS method to the 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs). On the basis of the original EDAS method, 2-tuple linguistic Pythagorean fuzzy EDAS (2TLPF-EDAS) method is built for MAGDM. Finally, a case study for brand packaging design effect evaluation show that the new method proposed in this paper is reasonable. Show more

Keywords: Multiple attribute group decision making (MAGDM), 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs), EDAS method, brand packaging design effect evaluation

DOI: 10.3233/JIFS-232054

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2167-2177, 2023