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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: Zhang, Guanhong | Brown, Peter | Li, Guobin
Article Type: Research Article
Abstract: With the maturity of virtualization technology, cloud computing has brought us new computing and service models. Adopting a resource pool solution based on cloud computing architecture, the virtualized resources can be uniformly managed and deployed to achieve the purpose of automated and intelligent management of information systems. However, because cloud servers have some features that are different from ordinary hosts, existing intrusion detection technologies cannot be directly applied to cloud computing. This paper focuses on the real-time dispatching of people. The main innovation of this paper is to apply BP neural network technology to the real-time dispatching of intelligent people, …establish the time prediction model of intelligent dispatching of people based on BP neural network, and design the intelligent dispatching algorithm of people based on BP neural network, and use examples to analyze the opposition to verify the feasibility of the algorithm. The results show that the algorithm improves the classification accuracy of neural networks and shortens the training time of samples. It improves the efficiency of intelligent dispatch detection, the accuracy of results and the efficiency of explicit algorithm. Show more
Keywords: Intelligent Scheduling, BP neural network, Cloud Computing, Real-time
DOI: 10.3233/JIFS-179158
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3545-3554, 2019
Authors: Sun, Bo | Wei, Ming | Yang, Chungfeng | Ceder, A.
Article Type: Research Article
Abstract: This paper presents a fuzzy optimization model for demand-responsive feeder transit services (DRT) that can transport an uncertain number of passengers from demand points to the rail station. The proposed model features fuzzy triangular number variables used to describe the changes in travel demand. Moreover, some practical factors such as boarding time windows and expected ride time are comprehensively considered in the model. The problem is formulated as a mixed-integer fuzzy expectation model to minimize the total travel distance for all routes, and its deterministic linear programming model is then obtained based on the credibility theory. Because the proposed model …is an extension of the NP-hard problem, this study involves the design of a collaborative ant colony optimization (ACO), which redefines the construct rules, pheromones, heuristic information, and selection strategies of solutions to address the limitations of traditional ACO such as the premature convergence. When ACO applied to a case study in Nanjing City, China, sensitivity analyses are performed to investigate the impact of the number of vehicles on results of the scheduling, compared with the traditional model. Finally, the proposed ACO is compared with ACO, standard ACO, particle swarm optimization (PSO), and genetic algorithm (GA) to prove its validity. Show more
Keywords: DRT transit system, fuzzy travel demand, ACO
DOI: 10.3233/JIFS-179159
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3555-3563, 2019
Article Type: Other
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3565-3565, 2019
Authors: Nayak, Byamakesh | Choudhury, Tanmoy Roy | Misra, Banishree | Mohapatra, Alivarani
Article Type: Research Article
Abstract: In this paper, component values of analog active filters are selected based on the manufacturer’s values of E series. The selection is based on optimization algorithms and here one is nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), and another one is the physics-based method called Sine Cosine Algorithm (SCA), are used for active filter design. The capability of optimization of the above algorithms is evaluated by considering the two active filters of a 4th order Butterworth and State variable filter. The performances of each algorithm are analyzed by applying to above two different filter structures, where the component …values are determined by making compatible with different E series manufacturer. Show more
Keywords: Active filter design, E series, sine cosine algorithm, whale optimization algorithm, 4th order butterworth filter, state variable filter
DOI: 10.3233/JIFS-171965
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3567-3579, 2019
Authors: Shi, Lukui | Du, Weifang | Li, Zhanru
Article Type: Research Article
Abstract: A two stage recognition method combined multiple kind of features was proposed to overcome the limitation of single kind of feature in the lung sound recognition. The method combines the improved Welch power spectrum, Mel cepstrum coefficients and the linear prediction cepstral coefficients based on the wavelet decomposition. In the first stage, pneumonia samples and asthma samples are firstly taken as the abnormal category. Then a two-class classifier based on random forests is trained to identify the normal samples and the abnormal samples. In the second stage, a classifier based on random forests is trained to recognize pneumonia and asthma …from the samples classified as the abnormal samples in the first stage. To further improve the accuracy, a multi granularity cycle segmentation method of lung sounds was presented, which is based on the short time zero crossing rate. It can better segment lung sounds. Experimental results showed that the proposed method greatly improved the recognition accuracy, especially for improving the accuracy of pneumonia and asthma. Show more
Keywords: Lung sound, random forest, Welch power spectrum, Mel cepstrum coefficient, linear prediction cepstral coefficient
DOI: 10.3233/JIFS-181339
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3581-3592, 2019
Authors: Wang, Guijun | Gao, Tong | Sun, Gang
Article Type: Research Article
Abstract: Fuzzy similarity degree is a measurement of the similarity between fuzzy sets through local information, it plays an important role in the design of fuzzy system and controller. This article first proposes a new computational formula for membership functions of a consequent fuzzy set based on fuzzy similarity degree, and an analytic representation of the Mamdani fuzzy system is obtained through the Gauss fuzzification, product inference engine and center average defuzzification. Next, a specific Mamdani fuzzy system constructed by Gauss fuzzifier or singleton fuzzification be expressed through a given fuzzy similarity degree in practice. Finally, the output algorithm of the …proposed fuzzy system is given by the space positioning method. The result shows that the Mamdani fuzzy system constructed by fuzzy similarity degree and Gauss fuzzification is superior to that based on singleton fuzzification in terms of approximation capability. Show more
Keywords: Fuzzy system, fuzzy similarity degree, Gauss fuzzification, singleton fuzzification, output algorithm
DOI: 10.3233/JIFS-181599
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3593-3603, 2019
Authors: Imran, Muhammad | Siddiqui, Muhammad Kamran | Baig, Abdul Qudair | Khalid, Waqas | Shaker, Hani
Article Type: Research Article
Abstract: Graph theory is a fundamental and energetic tool for designing and modeling a graph/network. There are certain topological indices based on degree, distance and eccentricity, etc. The topological indices essentially relate certain physio-concoction properties and bio-activity to the corresponding synthetic and atomic structure. In this paper, our aim is to figure out degree-based topological indices mainly atom-bond connectivity (ABC ), geometric-arithmetic (GA ), ABC 4 and GA 5 indices for cellular neural network (CNN) and give closed results of these indices for cellular neural network. Moreover, we also compute general Randi c ´ …index R α of CNN for α = { 1 , - 1 , 1 2 , - 1 2 } only and give analytical closed form results. A 3D graph analysis for comparison of indices is also given. Show more
Keywords: Molecular descriptor, cellular neural network, atom bond connectivity index, geometric arithmetic index, general Randić index
DOI: 10.3233/JIFS-181813
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3605-3614, 2019
Authors: Liu, Peide | Shen, Mengjiao
Article Type: Research Article
Abstract: As the extension of intuitionistic fuzzy numbers (IFNs), linguistic intuitionistic fuzzy numbers (LIFNs) are proposed. LIFNs are expressed by linguistic variables and take the membership degree (MD) and non-membership degree (NMD) into consideration. The MD and NMD of LIFNs can easier describe complex and fuzzy information in multiple attribute decision-making (MADM) problems. The TODIM method based on prospect theory can reflect the psychological factors of the decision makers (DMs). However, existing TODIM methods neither handle the decision-making problems under linguistic intuitionistic environment nor consider interrelations among multiple attributes. Based on these problems, in this paper, combining the fuzzy measure with …the TODIM method, an extended Choquet-TODIM method is proposed to process the MADM problems. The extended Choquet-TODIM method considers the interrelationship of multiple attributes and the bounded rationality of DMs. Firstly, the relative theories of LIFNs, the classical TODIM method and λ -fuzzy measures are briefly reviewed. Secondly, the TODIM method is extended to linguistic intuitionistic fuzzy environment and C-TODIM method of LIFNs is proposed. Then λ -fuzzy measure is extended to the classical TODIM method and a model of determining fuzzy measures is proposed. The proposed method gives the new solution to calculate the fuzzy measures and address the MADM problems with interrelationship among different attributes. Lastly, two numerical examples are used to compare with two existing methods and explain the effectiveness and superiority of this method. Show more
Keywords: Linguistic intuitionistic fuzzy numbers, TODIM method, fuzzy measures, multiple attribute decision making
DOI: 10.3233/JIFS-182554
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3615-3627, 2019
Authors: Shao, Ming-Wen | Wu, Wei-Zhi | Wang, Chang-Zhong
Article Type: Research Article
Abstract: There are mainly two classes of approaches in the studies of Formal Concept Analysis (FCA), i.e. the constructive and axiomatic approaches. In axiomatic approach, operators are interpreted by using operations in mathematical systems instead of operations in a formal context. Seeking for minimal axioms to characterize the concept generation operators is an important issue in the research of the axiomatic approach. In this paper, axiomatic characterizations of set-theoretic operators are investigated. We construct an adjoint generalized (dual) concept systems in which the pair of classical concept generation operators are represented by one set-theoretic operator, and the other operator can be …obtained from the former. Compared with the previous methods, the proposed generalized (dual) concept systems have fewer axioms and is easy to verify. Some properties of adjoint generalized (dual) concept systems are examined. Show more
Keywords: Concept lattice, galois connection, generalized concept system, set-theoretic operator
DOI: 10.3233/JIFS-182612
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3629-3638, 2019
Authors: Qu, Guohua | Li, Tianjiao | Qu, Weihua | Xu, Ling | Ma, Xiaolong
Article Type: Research Article
Abstract: Interval-value dual hesitant fuzzy set, first proposed by Ju et al. (Interval-valued dual hesitant fuzzy aggregation operators and their applications to multiple attribute decision making, 1203–1218, 2014). Multiple attribute decision making with dual hesitant fuzzy information is a new research topic since dual hesitant fuzzy set was firstly proposed, it has been widely studied in the fuzzy decision making literature. As a new generalization of fuzzy sets, interval-value dual hesitant fuzzy set (IVDHF) This article develops a multi-attribute decision making method considering the regret value theory and group satisfaction for the interval-value dual hesitant fuzzy element and incomplete weight information. …Considering that decision makers have different level of the degree of evaluation, firstly, based on the score function and the accuracy function of the interval-valued hesitant fuzzy element, the deviation function of the interval-valued hesitant fuzzy set is defined. On this basis, a new group satisfaction is proposed. And then, for the situation where the information of attribute weight is incompletely known and completely unknown, some optimization models of attribute weight are established by using the new group satisfaction degree, and then the attribute weight can be determined. Finally, a real example of investment alternative evaluation is carried out to validate the implementation of the proposed approach. Show more
Keywords: Interval-valued dual hesitant fuzzy set, group satisfaction degree, regret theory, stochastic multiple attribute decision making
DOI: 10.3233/JIFS-182634
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3639-3653, 2019
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