Journal of Intelligent & Fuzzy Systems - Volume 45, issue 1

Authors: Al-Sharqi, Faisal | Romdhini, Mamika Ujianita | Al-Quran, Ashraf

Article Type: Research Article

Abstract: A Q-neutrosophic soft environment is an innovative hybrid tool that combines features of both a Q-neutrosophic set (Q-NS) and a parametric tool “soft set” (SS) in order to manage imprecise and indeterminate situations in various mathematical problems. In this article, we introduce a new algebraic approach called Q-neutrosophic soft matrices (Q-NSMs) to address the issues of two-dimensional (two variables) in a universal set by representing the concept of Q-neutrosophic soft sets (Q-NSSs) in matrices. On Q-NSMs, we define the fundamental set operations and some algebraic operations, i.e., complement, union, intersection, addition, subtraction, multiplication, and scalar multiplication, and prove related properties …of these operations. Moreover, these operations are illustrated via several numerical examples. Then, two algorithms are proposed to tackle group decision making (GDM) problems: The first depends on the score function of Q-NSMs, and the second is based on the aggregation operator of Q-NSMs. Finally, this study is supported by a brief comparison with some relevant previous models. Show more

Keywords: Group decision-making, neutrosophic set, Q-Neutrosophic soft set, Q-Neutrosophic soft matrix, soft set

DOI: 10.3233/JIFS-224552

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 305-321, 2023

Authors: Zhao, Lei | Guo, Junmei | Sun, Kai

Article Type: Research Article

Abstract: Modern industrial processes often have nonlinearity, multivariate, time-delay, and measurement outliers, which make accurate data-driven modeling of key performance indicators difficult. To address these issues, a robust and regularized long short-term memory (LSTM) neural network for soft sensors in complex industrial processes was proposed. First, a conventional LSTM architecture was used as the basic model to deal with nonlinearity and time delay. Thereafter, a novel LSTM loss function that combines the excellent resistance to outliers of Huber M-Loss with the superior model reduction capability of ℓ1 regularization was designed. Subsequently, a backpropagation through time training algorithm for the proposed …LSTM was developed, including the chain derivative calculation and updating formulas. The adaptive moment estimation was applied to perform the gradient update, while the grid search and moving window cross-validation were used to find the optimal hyperparameters. Finally, nonlinear artificial datasets with time series and outliers, as well as an industrial dataset of a desulfurization process, were applied to investigate the performance of the proposed soft sensor. Simulation results show that the proposed algorithm outperforms other state-of-the-art soft sensors in terms of predictive accuracy and training time. The causal relationship of the data-driven soft sensor trained by the proposed algorithm is consistent with the field operation and chemical reactions of the desulfurization process. Show more

Keywords: Soft sensor, backpropagation through time, huber M-Loss, long short-term memory, ℓ1 regularization

DOI: 10.3233/JIFS-224557

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 323-343, 2023

Authors: Jeyalakshmi, P. | Karuppasamy, K.

Article Type: Research Article

Abstract: A signed graph Σ = (G , σ) is a graph with a sign attached to each arc. A subset S of V  (Σ) is called a dominating set of Σ if |N +  (v )  ∩ S | > |N -  (v )  ∩ S | for all v  ∈ V  - S  . A dominating set S  ⊆ V is a connected dominating set of Σ if <S > is connected. The minimum cardinality of a connected dominating set of Σ denoted by γsc , is called the connected domination number of Σ . In this paper, we introduce the connected domination number in a signed graph …Σ and study different bounds and characterization of the connected domination number in a signed graph Σ . Furthermore, we find the best possible upper and lower bounds for γ sc ( Σ ) + γ sc ( Σ α c ) where Σ is connected. Show more

Keywords: Signed graph, dominating set, connected dominating set, connected domination number

DOI: 10.3233/JIFS-223857

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 345-356, 2023

Authors: Reeba Jennifer, R. | Albert Raj, A.

Article Type: Research Article

Abstract: An Intracranial cyst is an abnormal growth of mass in the brain that affects functioning of the nervous system and so an early detection of the lesion enables to avoid adverse effects. The processing unit in the Magnetic Resonance Imaging (MRI) system performs reading the images followed by primary image enhancement to suppress distortions thereby enhancing the feature quality in terms of its intensity, augmenting the resolution by image segmentation, post-processing by thresholding based on grayscale values and performing several morphological operations. With the existing methodologies, extracting the Region Of Interest (ROI) with the overlapping intensity values lead to inaccurate …results. A novel method in which the input image that is anisotropically diffused and blurred is converted into a sharp image. Further, fuzzy partitioning of pixels deployed on Global Thresholding –Clustering Methodology (GT-CM) based segmentation takes 4 clusters into account hence forth seperating the exterior portion of the skull, the border region of the skull, the ventricles which may include the lesion and the noise. Statistical results based on several metrics such as sensitivity, specificity, F measure, Jaccord Index, Dice Coefficient and precision show that the proposed method is far more effective. An accuracy of 99.26% is obtained in exactly locating and extracting the lesion along with its attributes. Show more

Keywords: MRI, image segmentation, ROI, fuzzy, GT-CM

DOI: 10.3233/JIFS-221947

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 357-368, 2023

Authors: Bekhouche, Maamar | Haouassi, Hichem | Bakhouche, Abdelaali | Rahab, Hichem | Mahdaoui, Rafik

Article Type: Research Article

Abstract: Feature Selection (FS) for Sentiment Analysis (SA) becomes a complex problem because of the large-sized learning datasets. However, to reduce the data dimensionality, researchers have focused on FS using swarm intelligence approaches that reflect the best classification performance. Crocodiles Hunting Strategy (CHS), a novel swarm-based meta-heuristic that simulates the crocodiles’ hunting behaviour, has demonstrated excellent optimization results. Hence, in this work, two FS algorithms, i.e., Binary CHS (BCHS) and Improved BCHS (IBCHS) based on original CHS were applied for FS in the SA field. In IBCHS, the opposition-based learning technique is applied in the initialization and displacement phases to enhance …the search space exploration ability of the IBCHS. The two proposed approaches were evaluated using six well-known corpora in the SA area (Semeval-2016, Semeval-2017, Sanders, Stanford, PMD, and MRD). The obtained result showed that IBCHS outperformed BCHS regarding search capability and convergence speed. The comparison results of IBCHS to several recent state-of-the-art approaches show that IBCHS surpassed other approaches in almost all used corpora. The comprehensive results reveal that the use of OBL in BCHS greatly impacts the performance of BCHS by enhancing the diversity of the population and the exploitation ability, which improves the convergence of the IBCHS. Show more

Keywords: Sentiment analysis, Opinion mining, feature selection, swarm-based intelligence, crocodiles hunting strategy optimization algorithm, Opposition-based learning

DOI: 10.3233/JIFS-222192

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 369-389, 2023

Authors: Hatiboglu, Melek | Dayioglu, Habip | İssever, Halim | Ayvaz, Berk

Article Type: Research Article

Abstract: It is difficult to evaluate ergonomic risk factors in occupations with unpredictable tasks, random demands, and variable settings such as emergency medical services (EMS). This study deals with the problem of selecting an ergonomic risk-evaluation method with Pythagorean Fuzzy Sets (PFSs) based Pythagorean Fuzzy AHP (PF-AHP) and Pythagorean Fuzzy WASPAS (PF-WASPAS) methodology. The method selection criteria were obtained by consulting five different anonymous experts on the candidate criteria obtained from the literature review. The final four main criteria and ten sub-criteria were then decided. After the determination of the decision criteria, five experts were asked to evaluate the criteria and …to express their opinions on criteria-alternative scoring by means of a questionnaire for method selection. A two-step method is suggested for the selection of the ergonomic risk-evaluation method. In the first step, PF-AHP is utilized in order to identify the weight of criteria used in the method selection. In the second step, the PF-WASPAS method is proposed in order to OWAS, RULA, and REBA methods. The accuracy and validity of the suggested hybrid model is tested with real data in İstanbul Ambulance Service stations. A sensitivity analysis is carried out to test the reliability of the model. Moreover a comparative analysis is carried out with AHP and Fuzzy AHP methods to identify criteria weights. Study results show that REBA is the most appropriate ergonomic risk-evaluation method in EMS. Show more

Keywords: Ergonomic risk assessment method, Pythagorean fuzzy sets, AHP, WASPAS, emergency medical service

DOI: 10.3233/JIFS-222974

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 391-405, 2023

Authors: Meenakshi, A. | Mythreyi, O.

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-223484

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 407-420, 2023

Authors: Meenakshi, A. | Mythreyi, O. | Bramila, M. | Kannan, A. | Senbagamalar, J.

Article Type: Research Article

Abstract: Neutrosophic graphs deals with more complex, uncertain problems in real-life applications which provides more flexibility and compatibility than Intuitionistic fuzzy graphs. The aim of this paper is to enrich the efficiency of the network in accordance with productivity and quality. Here we develop two Neutrosophic graphs into a fully connected Neutrosophic network using the product of graphs. Such a type of network is formed from individuals with unique aspects in every field of work among them. This study proposes extending the other graph products and forming a single valued Neutrosophic graph to find the efficient productivity in the flow of …information on a single source network of a single valued Neutrosophic network. An Optimal algorithm is proposed and illustrated with an application. Show more

Keywords: Neutrosophic graph, graph operation, domination number, optimal network, score function

DOI: 10.3233/JIFS-223718

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 421-433, 2023

Authors: Dong, Qi | Gao, Yongli | Zhang, Wanhong | Chen, Zhipeng | Liu, Qian

Article Type: Research Article

Abstract: Radial distribution system is an important link connecting power supply and users, and its power supply reliability is directly related to users. Radial distribution network reconfiguration can transform the network structure by changing the switching state of the distribution network lines, and achieve the goals of reducing network operational losses, improving power quality, and power supply reliability while meeting various constraints such as radial operation, power supply and demand balance, capacity, and voltage. Radial distribution systems have the characteristics of multiple components and complex structures. How to quickly and accurately evaluate the health performance of radial distribution systems and find …an optimal solution for network reconfiguration are important issues in distribution network analysis. The network health performance evaluation of radial distribution system is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the network health performance evaluation of radial distribution system. In this paper, we extend the classical grey relational analysis (GRA) method to the probabilistic hesitancy fuzzy MAGDM with unknown weight information. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are briefly introduced. Then, the definition of the score values is employed to compute the attribute weights based on the information entropy method. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for network health performance evaluation of radial distribution system is designed to validate the proposed method and some comparative studies are also designed to verify the applicability. Show more

Keywords: Multiple attributes group decision making (MAGDM), probabilistic hesitant fuzzy sets, grey relational analysis method (GRA), information entropy, network health performance evaluation

DOI: 10.3233/JIFS-230028

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 435-443, 2023

Authors: Yang, Lan | Wang, Xiaofeng | Ding, Hongsheng | Yang, Yi | Zhao, Xingyu | Pang, Lichao

Article Type: Research Article

Abstract: Constraint satisfaction problems have a wide range of applications in areas such as basic computer theory research and artificial intelligence, and many major studies in industry are not solved directly, but converted into instances of satisfiability problems for solution. Therefore, the solution of the satisfiability problem is a central problem in many important areas in the future. A large number of solution algorithms for this problem are mainly based on completeness algorithms and heuristic algorithms. Intelligent optimization algorithms with heuristic policies run significantly more efficiently on large-scale instances compared to completeness algorithms. This paper compares the principles, implementation steps, and …applications of several major intelligent optimization algorithms in satisfiability problems, analyzes the characteristics of these algorithms, and focuses on the performance in solving satisfiability problems under different constraints. In terms of algorithms, evolutionary algorithms and swarm intelligence algorithms are introduced; in terms of applications, the solution to the satisfiability problem is studied. At the same time, the performance of the listed intelligent optimization algorithms in applications is analyzed in detail in terms of the direction of improvement of the algorithms, advantages and disadvantages and comparison algorithms, respectively, and the future application of intelligent optimization algorithms in satisfiability problems is prospected. Show more

Keywords: Constraint satisfaction problem, satisfiability problem, completeness algorithm, heuristic algorithm, intelligent optimization algorithms

DOI: 10.3233/JIFS-230073

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 445-461, 2023