Journal of Intelligent & Fuzzy Systems - Volume 44, issue 5

Authors: Deng, Yu

Article Type: Research Article

Abstract: The competitiveness evaluation of regional financial centers is frequently looked as the multiple attribute group decision-making (MAGDM) problem. Based on the TODIM method and fuzzy number intuitionistic fuzzy sets (FNIFS), this paper proposes a new FNIF-TODIM method to evaluate the competitiveness of regional financial centers. First, some basic theories related to FNIFS are briefly introduced. In addition, the weights of the attributes are obtained objectively using the CRITIC weighting method. Then, the traditional TODIM method is extended to FNIFS to obtain the final order of alternatives. As a result, all alternatives can be ranked and the best one for the …competitiveness assessment of regional financial centers can be identified. Finally, an example for competitiveness evaluation of regional financial centers and some decision comparative analysis is listed. The results show that the established algorithmic approach is useful. The main works of this work are: (1) the paper constructs the FNIF-TODIM method for the evaluation of the competitiveness of regional financial centers; (2) the established method is illustrated by a case study for competitiveness evaluation of regional financial centers; and (3) some comparisons prove the rationality and advantages. Show more

Keywords: Multiple attribute group decision making (MAGDM), fuzzy number intuitionistic fuzzy sets (FNIFSs), TODIM method, CRITIC method, Competitiveness evaluation

DOI: 10.3233/JIFS-221247

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7045-7057, 2023

Authors: Giri, Sourav Kumar | Garai, Totan | Islam, Sahidul

Article Type: Research Article

Abstract:  It is challenging for a decision-maker to decide a proper decision in severe situations of multi-aspirated real-life problems.So there is always an ambiguity in the mind of decision maker. Keeping such vagueness in mind, this paper aims to incorporate some situation parameters imprecise in nature. The imprecise parameters are taken in single-valued bipolar neutrosophic environments. Different arithmetic operations on the single-valued bipolar neutrosophic number using the (α , β) cut method are proposed in this paper. Using this we have calculated the possibility mean of single valued bipolar neutrosophic numbers. A multi-item economic production quantity model with one time only …discount is considered here with some parameters in single valued bipolar neutrosophic number as a case study of our proposed work. A possibilistic mean de-fuzzification technique is used here using possibility measures. Finally, numerical illustration and sensitivity analysis is done for different variables to emphasize the excellence of our proposed work. Show more

Keywords: Possibilistic mean, bipolar neutrosophic number, multi-item inventory model, one time only discount

DOI: 10.3233/JIFS-222752

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7059-7072, 2023

Authors: Satyanarayana Murthy, N. | Venkata Subbaiah, G.

Article Type: Research Article

Abstract: The minimal energy sensor nodes are critical to the long-term viability of any wireless sensor network WSN). Clustering is used for this purpose. Choosing an efficient Cluster Head (CH) is critical in such cluster-based networks, as they are accountable for aggregating and transmitting data from their associate nodes to the base station (BS). A Generative Adversarial Networks (GAN) is proposed in this work to improve the selection of CH. As part of the fitness function, nodes’ residual energy, average energy, and inter-cluster distance are all considered. In an effort to further reduce energy consumption, a GAN routing method is proposed …for use at the base station level for Efficient Energy. Simulations are used to evaluate the proposed ideal.The WSNs which require long life time with minimum cost sensors demand the proposed work. The research about the human unattainable places can be fit to necessitate this work. This method supports the maintenance of mines and petroleum refineries. In terms of energy consumption and network life expectancy, the results demonstrate a substantial improvement. And also, the proposed technique is analyzed and compared along with the existing approaches as Low-Energy Adaptive Clustering Hierarchy (Security based (S-LEACH), Cluster based (C-LEACH, More Energy Efficient-LEACH) (ME-LEACH) schemes. The proposed method detects the best location of storage-nodes for the sensor network. There is no need of agitation on battery drain up of storage-nodes (because of wireless recharge) which is a highly energy spending unit. The proposed method improves the network lifetime by a significant level. The proposed method is best fit to mines, petroleum refineries, forest department and military. The proposed method behaves as not only better storage scheme but also best fit to retrieval schemes. Show more

Keywords: Energy efficiency, generative adversarial networks, clustering, cluster heads, network life time, hierarchical routing

DOI: 10.3233/JIFS-223442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7073-7082, 2023

Authors: Shi, Zhengqi | Xie, Shurui | Li, Lingqiang

Article Type: Research Article

Abstract: The generalized neighborhood system-based rough set is an important extension of Pawlak’s rough set. The rough sets based on generalized neighborhood systems include two basic models: optimistic and pessimistic rough sets. In this paper, we give a further study on pessimistic rough sets. At first, to regain some properties of Pawlak’s rough sets that are lost in pessimistic rough sets, we introduce the mediate, transitive, positive (negative) alliance conditions for generalized neighborhood systems. At second, some approximation operators generated by special generalized neighborhood systems are characterized, which include serial, reflexive, symmetric, mediate, transitive, and negative alliance generalized neighborhood systems and …their combinations (e.g. reflexive and transitive). At third, we discuss the topologies generated by the upper and lower approximation operators of the pessimistic rough sets. Finally, combining practical examples, we apply pessimistic rough sets to rule extraction of incomplete information systems. Particularly, we prove that different decision rules can be obtained when different neighborhood systems are chosen. This enables decision makers to choose decisions based on personal preferences. Show more

Keywords: Rough set, multi-granulation rough sets, neighborhood system, approximation operator, axiomatic characterizations, information system

DOI: 10.3233/JIFS-222021

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7083-7097, 2023

Authors: Ganapathy, Revathy | Rajendran, Velayutham

Article Type: Research Article

Abstract: In current years, increased number of cyberspace users cause rapid ascends of network traffics. For instance: probability of receiving network traffic ever since software technologies that linked with devices produced massive amounts of data which are unable to accommodate through conventional schemes port based, payload based and machine learning approaches. Simultaneously SDN technology can alleviate problems of conventional method in classifying network traffic as malicious and benign, resources allocation, network monitoring along with enhancement in overall network performance via activist methods. This research work analyzed the net traffic metadata of 1,04,345 samples gathered from RYU-SDN controller, an OpenFlow controller using …mininet emulator with 23 features then performed encrypted metadata categorization into three classes namely TCP, UDP and ICMP attacks through deep CNN with two layers LSTM, CNN-two layers GRU and ConvNet Bidirectional with two layers GRU approaches with hyper parameters tuning appropriate for better network convergence, performance, optimization too. The proposed experimental outcomes reveals that deep based CB-GRU method fulfill traffic classification in SDN environment and accomplished significance enhancement in terms of accuracy 99.97%, and loss rate 0.01. Other evaluation criterias precision, recall, area under curve, were calculated for performance identification in net data traffic classification than conventional methods. Show more

Keywords: Software defined network (SDN), artificial intelligence (AI), ConvNet (CNN), long short term memory (LSTM), stochastic gradient descent (SGD) optimizer

DOI: 10.3233/JIFS-220051

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7099-7111, 2023

Authors: You, Yanlin | Wang, Zhenyu

Article Type: Research Article

Abstract: Point-of-interest (POI) recommendation has become one of the research highlights in the field of recommender systems due to the prosperity of location-based social networks in recent years. Various techniques have been proposed to improve the performance of the personalized recommendation service. Embedding-based methods have shown promising effect and attracted great attention for their flexibility and efficiency. Bayesian Personalized Ranking (BPR), as a famous optimization algorithm, has been widely used to learning the parameters of Embedding-based models in the recommendation scenario. However, existing Bayesian Personalized Ranking and its follow-up methods ignore the unique user preference when constructing the positive and negative …samples, leading a suboptimal performance. To overcome this limitation, we propose a novel method named preference-aware Bayesian Personalized Ranking (PABPR) according to empirical analyses on real-world datasets. The empirical analyses show that a user tend to visit a POI with categories which have been visited before. Thus, the key idea of PABPR is to introduce such user behaviors into the sample constructing process. PABPR is a general method which could be used for training various Embedding methods. Extensive experiments show that PABPR can lead a superior model performance compare to BPR and its variant methods. Show more

Keywords: Point-of-interest recommendation, user preference, Bayesian Personalized Ranking, embedding

DOI: 10.3233/JIFS-222705

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7113-7119, 2023

Authors: Xu, Aoqi | Tian, Man-Wen | Kausar, Nasreen | Mohammadzadeh, Ardashir | Pamucar, Dragan | Ozbilge, Ebru

Article Type: Research Article

Abstract: The financial systems have complicated dynamics and are perturbed by various uncertainties and disturbances. Chaos theory provides a practical approach to analyzing financial systems. The chaotic systems have unpredictable random characteristics that help to analyze the financial systems better. Recently, type-3 (T3) fuzzy logic systems (FLSs) have been developed for high-uncertain systems. T3-FLSs provide a reliable tool to cope with high-noisy environments. In T3-FLSs, the upper/lower bounds of uncertainties are fuzzy values. This property results in a strong tool to model more levels of uncertainties. Control, modeling, and forecasting accuracy in financial systems are so important. Then, better systems with …higher accuracy are required. In this paper, a new T3-FLS based controller is introduced for chaotic financial systems. By solving a Riccati equation, sufficient conditions are concluded for optimality and robustness. T3-FLSs are learned to minimize the error and stabilize the whole system. A new optimal learning rules are extracted for T3-FLSs. Various benchmark chaotic model of financial systems are considered for examining the efficacy of the introduced approach, and the excellent response and superiority of the suggested approach is verified. Also, a comparison with other methods demonstrates the better efficiency of the suggested scheme. Show more

Keywords: Fuzzy logic, financial systems, chaotic systems, optimal fuzzy control

DOI: 10.3233/JIFS-223396

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7121-7134, 2023

Authors: Jianfeng, Li | Xin, Chen | Hua, Guo | Guiling, Sun | Yuhua, Xu | Naizhen, Zhang

Article Type: Research Article

Abstract: The long-term maintenance of good condition for equipment is the basis of carrying out combat missions under the high technology and fast pace of modern war. However, the knowledge in the health management field at present has the characteristics of distribution, multi-source, heterogeneity and uncertainty, which seriously affects the efficiency of knowledge sharing and reuse. In order to improve the utilization of health management knowledge, an ontology-based knowledge representation method is proposed to describe knowledge in a unified and standardized way, and the classical ontology is extended to express the uncertain knowledge in the field of health management. In addition, …to improve the maintenance and knowledge updating efficiency, a global ontology model and a hierarchy, time and activity (HTA) ontology model are constructed. This paper takes the guidance subsystem of a missile as an example to illustrate the process of knowledge modeling. The results show this method realizes knowledge sharing in the health management field and can provide decision support for health management of equipment. Show more

Keywords: Knowledge representation, fuzzy ontology, HTA model, knowledge modeling

DOI: 10.3233/JIFS-224151

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7135-7152, 2023

Authors: Zhou, Jia-Jia | Zhu, Yi-An | Li, Lian | Shi, Xian-Chen

Article Type: Research Article

Abstract: The existing researchers generalize the decision-theoretic rough sets (DTRSs) model from the viewpoint of the cost function, whether the information system is complete, and so on. Few of them consider multiple different strategies to rank the expected losses. Furthermore, under the circumstance of Pythagorean fuzzy, we can’t directly define the partition of the objects set by employing equivalence relation, there is a need for constructing the general binary relation. Aiming at these problems, in present paper, we propose the similarity measure-based three-way decisions (3WD) in Pythagorean fuzzy information systems, both the binary relation and the similarity neighborhood are induced by …similarity measure between objects. Each object has its own losses, different strategies are designed to rank the expected losses. Further, the similarity measure-based DTRSs dealing with crisp concept and the similarity measure-based Pythagorean fuzzy DTRSs dealing with Pythagorean fuzzy concept are developed to establish the three regions of similarity measure-based 3WD. Finally, the proposed models are used to make decisions for classifying the network nodes of flying ad-hoc networks (FANETs) into normal nodes also called safe nodes, suspicious nodes, and malicious nodes also called unsafe nodes under the evaluation of Pythagorean fuzzy information. Show more

Keywords: Pythagorean fuzzy information systems, DTRSs, similarity measure-based 3WD, FANETs

DOI: 10.3233/JIFS-221424

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7153-7168, 2023

Authors: Leena Rosalind Mary, G. | Deepa, G.

Article Type: Research Article

Abstract: The first Zagreb index is equal to the sum of the squares of the degrees at each vertex of G. In this study, we create four distinct types of fuzzy transformation graphs and investigate the fundamental characteristics shared by them. Additionally, upper bounds on the first Zagreb index of fuzzy transformation graphs in terms of fuzzy graph G elements have been discovered.

Keywords: Fuzzy graph, fuzzy transformation graph, first Zagreb index

DOI: 10.3233/JIFS-221781

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7169-7180, 2023