Journal of Intelligent & Fuzzy Systems - Volume 40, issue 5

Authors: Chen, Huiping

Article Type: Research Article

Abstract:  This paper aims to put forward a hesitant fuzzy multi-attribute group decision making (MAGDM) method based on the weighted power aggregation operators in social network. From the point of view of social network analysis, decision makers (DMs) are interconnected in the process of MAGDM. Furthermore, the dimension of the obtained hesitant fuzzy element (HFE) by original power operators will be greater with the increasing number of attributes and alternatives and DMs, which will lead to the problem of “intermediate expression swell". This paper combines the order operation laws with the power operators to redefine two novel hesitant fuzzy power aggregation …operators to simplify the involved calculation and explore new operators’ properties. Meanwhile, when two given elements have different number of values, we use the strength of social ties and social influence to develop an algorithm for extending the HFEs objectively. On the other hand, the PageRank algorithm and the deviation method are used to determine DMs’ combined weights. The feasibility of the proposed hesitant fuzzy MAGDM method based on social network is illustrated by the application to the actual issue of decision making and the comparative analysis with the existing method. Show more

Keywords: Group decision making, hesitant fuzzy set, social network, power operator, PageRank algorithm

DOI: 10.3233/JIFS-201859

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9383-9401, 2021

Authors: Jia, Zhifu | Liu, Xinsheng | Zhang, Yu

Article Type: Research Article

Abstract: Uncertain pantograph differential equation (UPDE for short) is a special unbounded uncertain delay differential equation. Stability in measure, stability almost surely and stability in p -th moment for uncertain pantograph differential equation have been investigated, which are not applicable for all situations, for the sake of completeness, this paper mainly gives the concept of stability in distribution, and proves the sufficient condition for uncertain pantograph differential equation being stable in distribution. In addition, the relationships among stability almost surely, stability in measure, stability in p -th moment, and stability in distribution for the uncertain pantograph differential equation are also discussed.

Keywords: uncertainty theory, uncertain pantograph differential equation, stability in distribution, the relationships among stabilities

DOI: 10.3233/JIFS-201864

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9403-9411, 2021

Authors: Bhullar, Amrit Kaur | Kaur, Ranjit | Sondhi, Swati

Article Type: Research Article

Abstract: Today optimization algorithms are widely used in every application to increase quality, quantity and efficiency of making products as well as to minimize the production cost. Most of the techniques applied on different applications try to satisfy more than one parameter of interest in the design problem. In doing so, an objective function based on weighted aggregation has been designed to fulfill multi-objective optimization (MOO). A lot of computational time and energy is wasted in tuning the value of weighting factor in terms of number of trials each having hundreds of iterations to achieve the optimum solution. To reduce such …tedious practice of adjustment of weighting factor with multiple iterations, Fuzzy technique is proposed for auto-tuning of weighting factor in this paper that will benefit the researchers who are working upon optimization of their designed objectives using artificial intelligence techniques. This paper proposes MOO settlement method that does not require complex mathematical equations in order to simplify the weight finding problem of weighted aggregation objective function (WAOF). The results have been compared in terms of time and space efficiency to show the importance of Fuzzy-WAOF (F-WAOF). Further the results taken on Automatic Voltage Regulator (AVR) system for set point tracking, load disturbance, controller effort and modelling errors, prove the superior performance of the proposed method as compared to state of the art techniques. Show more

Keywords: Fuzzy technique, optimization techniques, weighted aggregation objective function (WAOF), weighting factor, automatic voltage regulator (AVR) system

DOI: 10.3233/JIFS-201911

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9413-9436, 2021

Authors: Durairaj, M. | Asha, J. Hirudhaya Mary

Article Type: Research Article

Abstract: Biometric features are used to verify the people identity in the living places like smart apartments. To increase the chance of classification and recognition rate, the recognizing procedure contains various steps such as detection of silhouette from the gait profile, silhouette segmentation, reading features from the silhouette, classification of features and finally recognition of person using its probability value. Person recognition accuracy will be oscillated and declined due to blockage, radiance and posture variance problems. In the proposed work, the gait profile will be formed by capturing the gait of a targeted person in stipulated time to reach the destination. …From the profile the silhouettes are detected using frame difference and segmented from the background using immediate thresholding and features are extracted from the silhouette using gray-level covariance matrix and optimized feature set is formed using PSO. These optimized features are fused, trained and classified using nearest neighbor support vectors. The fuzzy probability method is used for recognizing the person based on the probability value of the authentic and imposter scores. The relationship between the CMS, TPR, TNR and F-rate are calculated for 1 : 1 matcher from the gallery set. The performance of the classifiers are found to be perfect by plotting the DET graph and ROC curve. The proposed fuzzy probability theory is mingled with GLCMPSO and NSFV method for human recognition purpose. The performance of the proposed is proved to be acceptable for recognition with the optimal parameters (Entropy, SSIM, PSNR, CQM) calculation From the work, it is clear that, the rank probability is proportional to the match score value of the silhouette stored in the gallery. Show more

Keywords: Gait cycle, silhouette image, feature detection, feature extraction, feature classification, person recognition using fuzzy probability

DOI: 10.3233/JIFS-201913

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9437-9452, 2021

Authors: Kumar, Rajeev | Singh, Laxman | Tiwari, Rajdev

Article Type: Research Article

Abstract: Path planning for robots plays a vital role to seek the most feasible path due to power requirement, environmental factors and other limitations. The path planning for the autonomous robots is tedious task as the robot needs to locate a suitable path to move between the source and destination points with multifaceted nature. In this paper, we introduced a new technique named modified grey wolf optimization (MGWO) algorithm to solve the path planning problem for multi-robots. MGWO is modified version of conventional grey wolf optimization (GWO) that belongs to the category of metaheuristic algorithms. This has gained wide popularity for …an optimization of different parameters in the discrete search space to solve various problems. The prime goal of the proposed methodology is to determine the optimal path while maintaining a sufficient distance from other objects and moving robots. In MGWO method, omega wolves are treated equally as those of delta wolves in exploration process that helps in escalating the convergence speed and minimizing the execution time. The simulation results show that MGWO gives satisfactory performance than other state of art methods for path planning of multiple mobile robots. The performance of the proposed method is compared with the standard evolutionary algorithms viz., Particle Swarm Optimization (PSO), Intelligent BAT Algorithm (IBA), Grey Wolf Optimization (GWO), and Variable Weight Grey Wolf Optimization (VW-GWO) and yielded better results than all of these. Show more

Keywords: Meta-heuristic, particle swarm optimization, intelligent BAT algorithm, grey wolf optimization (GWO), modified grey wolf optimization (MGWO), variable weight grey wolf optimization (VW-GWO)

DOI: 10.3233/JIFS-201926

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9453-9470, 2021

Authors: Jin, Yilun | Liu, Yanan | Zhang, Wenyu | Zhang, Shuai | Lou, Yu

Article Type: Research Article

Abstract: With the advancement of machine learning, credit scoring can be performed better. As one of the widely recognized machine learning methods, ensemble learning has demonstrated significant improvements in the predictive accuracy over individual machine learning models for credit scoring. This study proposes a novel multi-stage ensemble model with multiple K-means-based selective undersampling for credit scoring. First, a new multiple K-means-based undersampling method is proposed to deal with the imbalanced data. Then, a new selective sampling mechanism is proposed to select the better-performing base classifiers adaptively. Finally, a new feature-enhanced stacking method is proposed to construct an effective ensemble model by …composing the shortlisted base classifiers. In the experiments, four datasets with four evaluation indicators are used to evaluate the performance of the proposed model, and the experimental results prove the superiority of the proposed model over other benchmark models. Show more

Keywords: Credit scoring, ensemble model, imbalanced learning, K-means, stacking

DOI: 10.3233/JIFS-201954

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9471-9484, 2021

Authors: Tang, Han | Li, Wenfei

Article Type: Research Article

Abstract: Interest rate, stock and option are all important parts of finance. This paper applies uncertain differential equation to the study of the evolution of interest rate and stock price separately. Based on actual observations, we estimate the parameters in uncertain differential equation with the method of moments. Using the introduced interest rate and stock models, we price European options and compare the results with actual observations. Finally, a paradox of the stochastic financial model is stated.

Keywords: Uncertain differential equation, geometric Liu process, uncertain exponential Ornstein-Uhlenbeck process, parameter estimation, European option pricing

DOI: 10.3233/JIFS-201955

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9485-9492, 2021

Authors: Nadeem, Asim | Kashif, Agha | Zafar, Sohail | Zahid, Zohaib

Article Type: Research Article

Abstract: The partition dimension is a variant of metric dimension in graphs. It has arising applications in the fields of network designing, robot navigation, pattern recognition and image processing. Let G  (V  (G ) , E  (G )) be a connected graph and Γ  = {P 1 , P 2 , …, P m } be an ordered m -partition of V  (G ). The partition representation of vertex v with respect to Γ is an m -vector r  (v |Γ ) = (d  (v , P 1 ) , d  (v , P 2 ) , …, d  (v , P m …)), where d  (v , P ) = min  {d  (v , x ) |x  ∈ P } is the distance between v and P . If the m -vectors r  (v |Γ ) differ in at least 2 positions for all v  ∈ V  (G ), then the m -partition is called a 2-partition generator of G . A 2-partition generator of G with minimum cardinality is called a 2-partition basis of G and its cardinality is known as the 2-partition dimension of G . Circulant graphs outperform other network topologies due to their low message delay, high connectivity and survivability, therefore are widely used in telecommunication networks, computer networks, parallel processing systems and social networks. In this paper, we computed partition dimension of circulant graphs C n  (1, 2) for n  ≡ 2 (mod 4), n  ≥ 18 and hence corrected the result given by Salman et al. [Acta Math. Sin. Engl. Ser. 2012, 28, 1851-1864]. We further computed the 2-partition dimension of C n  (1, 2) for n  ≥ 6. Show more

Keywords: Network topology design, Circulant graphs, partition dimension, k-partition dimension

DOI: 10.3233/JIFS-201982

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9493-9503, 2021

Authors: Wahid, Khola | Das, Angsuman | Rani, Anam | Amanat, Saira | Imran, Muhammad | Ali, Usman

Article Type: Research Article

Abstract: There are several approaches to lower the complexity of huge networks. One of the key notions is that of twin nodes, exhibiting the same connection pattern to the rest of the network. We extend this idea by defining a twin preserving spanning subgraph (TPS-subgraph) of a simple graph as a tool to compute certain graph related invariants which are preserved by the subgraph. We discuss how these subgraphs preserve some distance based parameters of the simple graph. We introduce a sub-skeleton graph on a vector space and examine its basic properties. The sub-skeleton graph is a TPS-subgraph of the non-zero …component graph defined over a vector space. We prove that some parameters like the metric-dimension are preserved by the sub-skeleton graph. Show more

Keywords: Basis, graph, independent set, maximal clique, metric-dimension, twins, 05C12, 05C35

DOI: 10.3233/JIFS-201989

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9505-9513, 2021

Authors: Zeng, Qingtian | Zhao, Xishi | Hu, Xiaohui | Duan, Hua | Zhao, Zhongying | Li, Chao

Article Type: Research Article

Abstract: Word embeddings have been successfully applied in many natural language processing tasks due to its their effectiveness. However, the state-of-the-art algorithms for learning word representations from large amounts of text documents ignore emotional information, which is a significant research problem that must be addressed. To solve the above problem, we propose an emotional word embedding (EWE ) model for sentiment analysis in this paper. This method first applies pre-trained word vectors to represent document features using two different linear weighting methods. Then, the resulting document vectors are input to a classification model and used to train a text sentiment classifier, …which is based on a neural network. In this way, the emotional polarity of the text is propagated into the word vectors. The experimental results on three kinds of real-world data sets demonstrate that the proposed EWE model achieves superior performances on text sentiment prediction, text similarity calculation, and word emotional expression tasks compared to other state-of-the-art models. Show more

Keywords: Sentiment analysis, word embedding, classification, representation learning

DOI: 10.3233/JIFS-201993

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9515-9527, 2021