Journal of Intelligent & Fuzzy Systems - Volume 42, issue 3

Authors: Xu, Binbin | Chen, Chang | Tang, Jinrui | Tang, Ruoli

Article Type: Research Article

Abstract: Due to the increasingly demand of wireless broadband applications in modern society, the device-to-device (D2D) communication technique plays an important role for improving communication spectrum efficiency and quality of service (QoS). This study focuses on the optimal allocation of link resource in D2D communication systems using intelligent approaches, in order to obtain optimal energy efficiency of D2D-pair users (DP) and also ensure communication QoS. To be specific, the optimal resource allocation (ORA) model for ensuring the cooperation between DP and cellular users (CU) is established, and a novel coding strategy of ORA model is also proposed. Then, for efficiently optimizing …the ORA model, a novel swarm-intelligence-based algorithm called the dynamic topology coevolving differential evolution (DTC-DE) is developed, and the efficiency of DTC-DE is also tested by a comprehensive set of benchmark functions. Finally, the DTC-DE algorithm is employed for optimizing the proposed ORA model, and some state-of-the-art algorithms are also employed for comparison. Result of case study shows that the DTC-DE outperforms its competitors significantly, and the optimal resource allocation can be obtained by DTC-DE with robust performance. Show more

Keywords: Device-to-device communication, intelligent communication system, communication resource allocation, differential evolution, swarm intelligence

DOI: 10.3233/JIFS-211008

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1607-1621, 2022

Authors: Tong, Huagang | Zhu, Jianjun | Yi, Yang

Article Type: Research Article

Abstract: Sharing economy is significant for economic development, stable matching plays an essential role in sharing economy, but the large-scale sharing platform increases the difficulties of stable matching. We proposed a two-sided gaming model based on probabilistic linguistic term sets to address the problem. Firstly, in previous studies, the mutual assessment is used to obtain the preferences of individuals in large-scale matching, but the procedure is time-consuming. We use probabilistic linguistic term sets to present the preferences based on the historical data instead of time-consuming assessment. Then, to generate the satisfaction based on the preference, we regard the similarity between the …expected preferences and actual preferences as the satisfaction. Considering the distribution features of probabilistic linguistic term sets, we design a shape-distance-based method to measure the similarity. After that, the previous studies aimed to maximize the total satisfaction in matching, but the individuals’ requirements are neglected, resulting in a weak matching result. We establish the two-sided gaming matching model from the perspectives of individuals based on the game theory. Meanwhile, we also study the competition from other platforms. Meanwhile, considering the importance of the high total satisfaction, we balance the total satisfaction and the personal requirements in the matching model. We also prove the solution of the matching model is the equilibrium solution. Finally, to verify the study, we use the experiment to illustrate the advantages of our study. Show more

Keywords: Sharing economy, two-sided gaming matching, shape-distance-based similarity, probabilistic linguistic term sets, efficient sharing

DOI: 10.3233/JIFS-211042

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1623-1641, 2022

Authors: Li, Wenwen | Yin, Shiqun | Pu, Ting

Article Type: Research Article

Abstract:  The purpose of aspect-based sentiment analysis is to predict the sentiment polarity of different aspects in a text. In previous work, while attention has been paid to the use of Graph Convolutional Networks (GCN) to encode syntactic dependencies in order to exploit syntactic information, previous models have tended to confuse opinion words from different aspects due to the complexity of language and the diversity of aspects. On the other hand, the effect of word lexicality on aspects’ sentiment polarity judgments has not been considered in previous studies. In this paper, we propose lexical attention and aspect-oriented GCN to solve the …above problems. First, we construct an aspect-oriented dependency-parsed tree by analyzing and pruning the dependency-parsed tree of the sentence, then use the lexical attention mechanism to focus on the features of the lexical properties that play a key role in determining the sentiment polarity, and finally extract the aspect-oriented lexical weighted features by a GCN.Extensive experimental results on three benchmark datasets demonstrate the effectiveness of our approach. Show more

Keywords: Sentiment analysis, GCN, lexical attention, dependency parsing

DOI: 10.3233/JIFS-211045

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1643-1654, 2022

Authors: Yang, Ziyu | Zhang, Liyuan | Li, Tao

Article Type: Research Article

Abstract: Interval-valued Pythagorean fuzzy preference relation (IVPFPR) plays an important role in representing the complex and uncertain information. The application of IVPFPRs gives better solutions in group decision making (GDM). In this paper, we investigate a new method to solve GDM problems with IVPFPRs. Firstly, novel multiplicative consistency and consensus measures are proposed. Subsequently, the procedure for improving consistency and consensus levels are put forward to ensure that every individual IVPFPR is of acceptable multiplicative consistency and consensus simultaneously. In the context of minimizing the deviations between the individual and collective IVPFPRs, the objective experts’ weights are decided according to the …optimization model and the aggregated IVPFPR is derived. Afterwards, a programming model is built to derive the normalized Pythagorean fuzzy priority weights, then the priority weights of alternatives are identified as well. An algorithm for GDM method with IVPFPRs is completed. Finally, an example is cited and comparative analyses with previous approaches are conducted to illustrate the applicability and effectiveness of the proposed method. Show more

Keywords: Group decision making, interval-valued pythagorean fuzzy preference relation, multiplicative consistency, consensus

DOI: 10.3233/JIFS-211131

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1655-1677, 2022

Authors: Wang, Jianfeng | Wang, Ruomei | Liu, Shaohui

Article Type: Research Article

Abstract: Session-based recommendation is an overwhelming task owing to the inherent ambiguity in anonymous behaviors. Graph convolutional neural networks are receiving wide attention for session-based recommendation research for the sake of their ability to capture the complex transitions of interactions between sessions. Recent research on session-based recommendations mainly focuses on sequential patterns by utilizing graph neural networks. However, it is undeniable that proposed methods are still difficult to capture higher-order interactions between contextual interactions in the same session and has room for improvement. To solve it, we propose a new method based on graph attention mechanism and target oriented items to …effectively propagate information, HOGAN for brevity. Higher-order graph attention networks are used to select the importance of different neighborhoods in the graph that consists of a sequence of user actions for recommendation applications. The complementarity between high-order networks is adopted to aggregate and propagate useful signals from the long distant neighbors to solve the long-range dependency capturing problem. Experimental results consistently display that HOGAN has a significantly improvement to 71.53% on precision for the Yoochoose1_64 dataset and enhances the property of the session-based recommendation task. Show more

Keywords: Long-range dependency, higher-order network, context-aware, intelligent recommendation

DOI: 10.3233/JIFS-211155

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1679-1691, 2022

Authors: Yang, Bo | Xu, Kaiyong | Wang, Hengjun | Zhang, Hengwei

Article Type: Research Article

Abstract: Deep neural networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding small, human-imperceptible perturbations to the original images, but make the model output inaccurate predictions. Before DNNs are deployed, adversarial attacks can thus be an important method to evaluate and select robust models in safety-critical applications. However, under the challenging black-box setting, the attack success rate, i.e., the transferability of adversarial examples, still needs to be improved. Based on image augmentation methods, this paper found that random transformation of image brightness can eliminate overfitting in the generation of adversarial examples and improve their transferability. In light of …this phenomenon, this paper proposes an adversarial example generation method, which can be integrated with Fast Gradient Sign Method (FGSM)-related methods to build a more robust gradient-based attack and to generate adversarial examples with better transferability. Extensive experiments on the ImageNet dataset have demonstrated the effectiveness of the aforementioned method. Whether on normally or adversarially trained networks, our method has a higher success rate for black-box attacks than other attack methods based on data augmentation. It is hoped that this method can help evaluate and improve the robustness of models. Show more

Keywords: Adversarial examples, black-box attacks, deep neural networks (DNNs)

DOI: 10.3233/JIFS-211157

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1693-1704, 2022

Authors: Jiang, Nan-Yun | Yan, Hong-Sen

Article Type: Research Article

Abstract: For the fixed-position assembly workshop, the integrated optimization problem of production planning and scheduling in the uncertain re-entrance environment is studied. Based on the situation of aircraft assembly workshops, the characteristics of fixed-position assembly workshop with uncertain re-entrance are abstracted. As the re-entrance repetition obeys some type of probability distribution, the expected value is used to describe the repetition, and a bi-level stochastic expected value programming model of integrated production planning and scheduling is constructed. Recursive expressions for start time and completion time of assembly classes and teams are confirmed. And the relation between the decision variable in the lower-level …model of scheduling and the overtime and earliness of assembly classes and teams in the upper-level model of production planning is identified. Addressing the characteristics of bi-level programming model, an alternate iteration method based on Improved Genetic Algorithm (AI-IGA) is proposed to solve the models. Elite Genetic Algorithm (EGA) is introduced for the upper-level model of production planning, and Genetic Simulated Annealing Algorithm based on Stochastic Simulation Technique (SS-GSAA) is developed for the lower-level model of scheduling. Results from our experiments demonstrate that the proposed method is feasible for production planning and optimization of the fixed-position assembly workshop with uncertain re-entrance. And algorithm comparison verifies the effectiveness of the proposed algorithm. Show more

Keywords: Uncertain re-entrance, fixed-position assembly workshop, integrated optimization of production planning and scheduling, improved genetic algorithm

DOI: 10.3233/JIFS-211159

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1705-1722, 2022

Authors: Jiang, Zhiwei | Wei, Guiwu | Chen, Xudong

Article Type: Research Article

Abstract: For the long-term development of shopping mall, the managers of shopping mall tend to build a new store to expand the enterprise’s market share in a new city. After holding a preliminary survey of the city, managers have initially identified five sites for construction. In order to select an optimal site, managers invite four experts who come from university, marking statistics, corporate executives and accounting to score sites. And they choose the best site on the basis of scores. The trait of EDAS method is to select an optimal alternative by using the distance of each alternative from the first-rank …value. In this manuscript, we build the picture fuzzy EDAS method based on the cumulative prospect theory (PF-CPT-EDAS) for multiple attribute group decision-making (MAGDM) and it can help managers to choose an optimal alternative effectively. During the procedure of PF-CPT-EDAS means, we take advantage of the entropy means to calculate the original weights of all attributes. Ultimately, we testify the effectiveness of the novel model by comparing the overcome of PF-CPT-EDAS means with the results of PF-EDAS approach and other methods. Show more

Keywords: Multiple attribute group decision-making (MAGDM), picture fuzzy sets (PFSs), EDAS method, cumulative prospect theory (CPT), site selection

DOI: 10.3233/JIFS-211171

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1723-1735, 2022

Authors: Fan, Jianping | Zhai, Shanshan | Wu, Meiqin

Article Type: Research Article

Abstract: Neutrosophic cubic set (NCS) can process complex information by combining interval neutrosophic set and single-valued neutrosophic set. It can simultaneously describe the uncertain and certain part of information. Prospect theory (PT) is based on bounded rationality and can reflect decision maker’s different risk attitudes to gains and losses. Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method can measure and rank the alternatives according to compromise solution. Considering the bounded rationality of decision makers and compromise solution of alternatives, this paper combines the PT with MARCOS method to neutrosophic cubic environment to solve multi-attribute decision-making problem. First, the …theoretical basis of NCS is introduced. Second, the PT and MARCOS method are combined. To reflect subjective views of decision makers and the objectivity of decision-making information, this paper uses geometric average method to combine subjective weights (calculated by the best-worst method) and objective weights (calculated ed by the entropy method). Then, the PT-MARCOS method is applied to a decision-making problem. Further, a sensitivity analysis is conducted to study the influence of different attenuation factor values and different expectation coefficient on the ranking; and through comparative analysis to illustrate the superiority of the PT-MARCOS method. Finally is the conclusion. Show more

Keywords: Multi-attribute decision-making, neutrosophic cubic set, prospect theory, measurement of alternatives and ranking according to compromise solution, best-worst method

DOI: 10.3233/JIFS-211189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1737-1748, 2022

Authors: Kumar, Satish | Gupta, Sunanda | Arora, Sakshi

Article Type: Research Article

Abstract: Network Intrusion detection systems (NIDS) detect malicious and intrusive information in computer networks. Presently, commercial NIDS is based on machine learning approaches that have complex algorithms and increase intrusion detection efficiency and efficacy. These machine learning-based NIDS use high dimensional network traffic data from which intrusive information is to be detected. This high-dimensional network traffic data in NIDS needs to be preprocessed and normalized to make it suitable for machine learning tools. A machine learning approach with appropriate normalization and prepossessing increases NIDS performance. This paper presents an empirical study on various normalization methods implemented on a benchmark network traffic …dataset, KDD Cup’99, that has been used to evaluate the NIDS model. The present study shows decimal normalization has a better prediction performance than non-normalized traffic data categorized into ‘normal’ or ‘intrusive’ classes. Show more

Keywords: Intrusion detection system, machine learning, normalization, classification, KDD cup’99 dataset

DOI: 10.3233/JIFS-211191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1749-1766, 2022