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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Si, Guangsen | Liao, Huchang | Yu, Dejian | Llopis-Albert, Carlos
Article Type: Research Article
Abstract: The hesitant fuzzy linguistic term sets can retain the completeness of linguistic information elicitation by assigning a set of possible linguistic terms to a qualitative variable. However, sometimes experts cannot make sure that the objects attain these possible linguistic terms but only provide the degrees of confidence to express their hesitant cognition. Given that the interval numbers can denote the possible membership degrees that an object belongs to a set, it is suitable and convenient to provide an interval-valued index to measure the degree of a linguistic variable to a given hesitant fuzzy linguistic term set. Inspired by this idea, …we introduce the concept of interval-valued 2-tuple hesitant fuzzy linguistic term set (IV2THFLTS) based on the interval number and the hesitant fuzzy linguistic term set. Then, we define some interval-valued 2-tuple hesitant fuzzy linguistic aggregation operators. Afterwards, to overcome the instability of subjective weights, we propose a method to compute the weights of attributes. For the convenience of application, a method is given to solve the multiple attribute decision making problems with IV2THFLTSs. Finally, a case study is carried out to validate the proposed method, and some comparisons with other methods are given to show the advantages of the proposed method. Show more
Keywords: Hesitant fuzzy linguistic term sets, interval numbers, interval-valued 2-tuple hesitant fuzzy linguistic term set, aggregation operators, weight determining method, oversea investment evaluation
DOI: 10.3233/JIFS-171967
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4225-4236, 2018
Authors: Chen, Yanyan | Wang, Kuaini | Zhong, Ping
Article Type: Research Article
Abstract: One-class classification is an important problem encountered in a lot of applications. The datasets extracted from the real-world problems are often represented as tensors. The classical support vector domain description (SVDD) for one-class classification problems cannot work directly since its inputs are vectors. This paper develops a linear tensor-based algorithm named as Linear Support Tensor Domain Description (LSTDD) to find a closed hypersphere with the minimal volume in the tensor space which can contain almost entirely of the target samples. LSTDD can keep data topology and make the parameters need to be estimated less, and it is more suitable for …learning the high dimensional and small sample size problem. Firstly, we detail the LSTDD model with 2nd-order tensors, and then extend it to the higher order tensors. It has been shown by experiments on the real-world datasets that LSTDD is a promising method for handling one-class classification problems with both 2nd-order and higher order tensor inputs. Show more
Keywords: One-class classification, support vector domain description, support tensor machine, support tensor domain description
DOI: 10.3233/JIFS-17325
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4237-4247, 2018
Authors: Chen, Lin | Peng, Jin | Rao, Congjun | Rosyida, Isnaini
Article Type: Research Article
Abstract: With the increasing of the complexity of a system, there is a variety of indeterminacy in the practical applications of graph theory. We focus on uncertain random graph, in which some edges exist with degrees in probability measure and others exist with degrees in uncertain measure. In this paper, the chance theory is applied to construct the cycle index of an uncertain random graph. Then a method to calculate the cycle index of an uncertain random graph is presented. We also discuss some properties of the cycle index.
Keywords: Cycle index, uncertain random graph, chance theory, uncertainty theory
DOI: 10.3233/JIFS-17373
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4249-4259, 2018
Authors: Sheng, Yuhong | Shi, Gang
Article Type: Research Article
Abstract: Asian option is known as a derivation financial product. And uncertain finance takes uncertain situation into account, and there comes uncertain stock models based on uncertain theory. This paper follows the mean-reverting stock model which based in uncertain situations presented by Liu. The mean-reverting model under asian option is discussed in this paper. This paper deals with the problem of pricing an Asian currency option. Based on the principle of making fair deal, the pricing formula is verified. Furthermore, a simple discussions about the situation of single variable in the option pricing model are also drawn in this paper. Basic …relations between parameters and result are also discussed. Show more
Keywords: Option pricing, currency model, uncertain parameters, uncertain differential equation
DOI: 10.3233/JIFS-17536
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4261-4268, 2018
Authors: Shi, Fu-Gui | Wang, Kai
Article Type: Research Article
Abstract: In this paper, the concept of M -fuzzifying geodesic interval operators is introduced in M -fuzzifying metric spaces. It is a generalization of geodesic interval operators in metric spaces. And an M -fuzzifying geometric characterization of M -fuzzifying geodesic interval operators is obtained. Based on M -fuzzifying geodesic interval operators, M -fuzzifying geodesic convexities can be induced.
Keywords: M-fuzzifying metric, M-fuzzifying convexity, M-fuzzifying geodesic interval operator, fuzzy partial order
DOI: 10.3233/JIFS-17617
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4269-4277, 2018
Authors: Dutta, Hemen | Gogoi, Jyotishmaan
Article Type: Research Article
Abstract: In this paper, we first study the notion of almost convergence of double sequences of fuzzy numbers using the idea of Pringsheim ’s convergence and compare with the set of bounded double sequences of fuzzy numbers. The primary aim is to characterize matrix classes involving some sets of double sequences of fuzzy numbers and also the set of almost convergent double sequence of fuzzy numbers. The approach adopted in the investigation of main results should be helpful to develop theories to deal with fuzzification of summability theory and its applications.
Keywords: Double sequences of fuzzy numbers, Pringsheim’s convergence and almost convergence, algebraic duals, four-dimensional infinite matrix of fuzzy numbers, matrix transformations
DOI: 10.3233/JIFS-17629
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4279-4290, 2018
Authors: Mu, Huiyu | Xu, Jiucheng | Wang, Yun | Sun, Lin
Article Type: Research Article
Abstract: The selection of feature genes with high recognition ability from the gene expression profiles have gained great significances in biology. However, most of the existing methods for feature genes selection have a high time complexity where lead to a poor performance. Motivated by this, an effective feature selection method, called Fisher transformation (FT), is proposed which based on the improved Fisher discriminant analysis (FDA) and neighborhood rough set algorithms. The FT method has two benefits: 1. The multiple neighborhood rough set algorithm is used for solving the small sample size problem of FDA; 2. The improved FDA algorithm is used …for selecting feature genes and ameliorating poor ability of classification. Furthermore, we measure the impact of the FT approach on the final selection consequence. The results obtained on four public tumor microarray datasets provide beneficial insight on both the benefits and limitations, paving the way to the exploration of new and wider feature selection programs. Show more
Keywords: Fisher discriminant analysis, neighborhood rough set, feature selection, Fisher transformation
DOI: 10.3233/JIFS-17710
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4291-4300, 2018
Authors: Li, Jinquan | Xu, Dehua | Li, Hongxing
Article Type: Research Article
Abstract: In recent years, due window assignment scheduling problems deriving from just-in-time supply chain management have been studied extensively. However, precedence constraints and uncertain processing times of jobs are rarely involved simultaneously in the studies. In this paper, a single machine due window assignment scheduling problem with uncertain processing times, precedence constraints and due window size constraints is investigated, in which the processing times of jobs are presented by fuzzy numbers. The objective is to minimize the mean value of the total earliness-tardiness penalties. An optimal polynomial time algorithm is proposed for the problem when there are no precedence constraints among …jobs. Note that the problem with general precedence constraints is NP-hard. An efficient 2-approximation algorithm is proposed for the general constraint problem based on linear programming relaxation. The experimental results show that the proposed methods are effective and promising. Show more
Keywords: Fuzzy set, fuzzy number, possibilistic mean value and variance, due window assignment scheduling, precedence constraints
DOI: 10.3233/JIFS-17766
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4301-4314, 2018
Authors: Banumalar, K. | Manikandan, B.V. | Arul Jeyaraj, K. | Chandrasekaran, K.
Article Type: Research Article
Abstract: This paper presents a new multi-objective problem formulation based optimal placement of Phasor Measurement Units (PMUs) considering the power system observability and reliability conditions. In this proposed method, Optimal Placement of PMUs (OPP) are determined to satisfy two objectives simultaneously such as minimizing the number of PMUs for achieving the complete observability and maximizing the reliability for better operation of power systems. Since the above two objectives are conflicting in nature, Fuzzified Clustered Gravitational Search Algorithm (FCGSA) is proposed to solve Multi-objective Optimal Placement of PMUs (MOPP) problem to provide a good tradeoff solution between the competing objectives. The fuzzy …membership for each objective function is designed and proposed to determine the best solution of MOPP problem. Conventional rules are applied to minimize the number of PMUs and a new rule is developed to maximize the observability as well as reliability of the power systems. It helps the system operators to make necessary remedial actions to prevent the outage of the low reliability bus. The proposed method is validated on IEEE 14, 30 and 57 bus systems. The most effective strategy of allocating the optimal number of PMUs and their locations is demonstrated by comparing its performance with other methods reported in the available literatures. Show more
Keywords: Phasor measurement unit, optimal placement, clustered gravitational search algorithm, fuzzy set theory, multi-objective problem
DOI: 10.3233/JIFS-17800
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4315-4330, 2018
Authors: Sorna Keerthi, R. | Meena Alias Jeyanthi, K.
Article Type: Research Article
Abstract: LTE-A downlink transfers data and control information from base station to mobile. To reduce the mean square error between original and estimated channel, pilot/training based channel estimation like Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE) are ubiquitous for most wireless standards. To optimize the channel, many intelligent optimized techniques were developed. GA has no guarantee in finding global optima and high convergence time. ANN suits only linear solutions and more training period. PSO fits high dimensional space but needs more iterations. ABC has limited search space by initial solution. CS requires large resources and high computational …time. To overcome these effects, an effortless Trellis Coded Firefly Optimized LMMSE based algorithm is proposed to estimate the channel. TCM has high spectral efficiency, more data rate and reduced error. FA has low complexity, easy implementation, automatic subdivision of groups to find local/global optima and ability to deal with multimodality. At SNR = 10 dB, LSE has high MSE of 10–2 , LMMSE has 15.85% reduced MSE than LSE. The previous optimized methods have MSE ranging from 10–3 to 10–2 but the proposed method with 64-QAM has MSE range of 10–5 to 10–4 , which is 100 times reduced. Show more
Keywords: LTE-A downlink, trellis coder, firefly algorithm, channel estimation, mean square error
DOI: 10.3233/JIFS-17840
Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4331-4344, 2018
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