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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: Tripura, P. | Babu, Y. Srinivasa Kishore
Article Type: Research Article
Abstract: This paper presents simulation of speed control of Separately Excited DC Motor (SEDM) using Neuro-Fuzzy Controller. The Controller is based on Adaptive Neuro Fuzzy Inference System (ANFIS) which aims at reducing peak-over shoot and settling time of DC Motor. The performance of the driver system was evaluated through the simulations using MATLAB/SIMULINK. The simulation results shows that the performance of the drive with ANFIS Controller outperforms the performance of the DC Motor with conventional PI Controller.
Keywords: SEDM, PI controller and ANFIS Controller
DOI: 10.3233/IFS-120729
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 223-227, 2014
Authors: Qamar, Usman
Article Type: Research Article
Abstract: According to the definition of cluster objects belonging to same cluster must have high similarity while objects belonging to different clusters should be highly dissimilar. In the same way cluster validity indices for analyzing clustering result are based on the same two properties of cluster i.e. compactness (intra-cluster similarity) and separation (inter-cluster dissimilarity). Most of the clustering algorithm developed so far focuses only on minimizing the within cluster distance. Almost all clustering algorithms ignore to include the second property of a cluster i.e. to produce highly dissimilar clusters. This paper recommends and incorporates a dissimilarity measure in Fuzzy c-means (FCM) …clustering algorithm, a well-known and widely used algorithm for data clustering, to analyze the benefit of considering second property of cluster. Here we also introduced a new effective way of incorporating the effect of such measures in a clustering algorithm. Experimental results on both synthetic and real datasets had shown the better performance attained by the new improved Fuzzy c-means in comparison to classical Fuzzy c-means algorithm. Show more
Keywords: Clustering, fuzzy c-means, cluster validity indices, dissimilarity measure
DOI: 10.3233/IFS-120730
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 229-238, 2014
Authors: Tang, Jian | Xie, Xiangyun
Article Type: Research Article
Abstract: Let S be an ordered semigroup. In this paper we first introduce the concepts of (∈, ∈ ∨ qk )-fuzzy ideals, (∈, ∈ ∨ qk )-fuzzy bi-ideals and (∈, ∈ ∨ qk )-fuzzy generalized bi-ideals of an ordered semigroup S by the ordered fuzzy points of S, and investigate their related properties. Furthermore, characterizations of regular ordered semigroups by the properties of (∈, ∈ ∨ qk )-fuzzy left ideals, (∈, ∈ ∨ qk )-fuzzy right ideals and (∈, ∈ ∨ qk )-fuzzy (generalized) bi-ideals are given.
Keywords: Regular ordered semigroup, intra-regular ordered semigroup, strongly convex fuzzy subset, $(\in, \in \vee q_k)$-fuzzy left (right) ideal, $(\in, \in \vee q_k)$-fuzzy (generalized) bi-ideal
DOI: 10.3233/IFS-120731
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 239-252, 2014
Authors: Meddeb, Olfa | Ben Abdelaziz, Fouad | Figueira, José Rui
Article Type: Research Article
Abstract: In many social decision making contexts, a manipulator attempts to change the social choice in his favor by misrepresenting his preferences. This paper deals with the strategic manipulation problem of social choice functions aggregating fuzzy individual preferences. It defines how the strategic misrepresentation of fuzzy preferences can be profitable for an individual with a fuzzy weak preference relation. The case of max-$\top$-transitive fuzzy preference relations is considered where $\top$ is a t-norm. Then, the impossibility of building a non-manipulable fuzzy social choice function except the dictatorial one is established, generalizing thus the well-known Gibbard-Satterthwaite's result. The obtained results generalizes also …the one of Ben Abdelaziz et al. for max-min transitive fuzzy preference relations. Show more
Keywords: Fuzzy preference relation, fuzzy social choice functions, strategic manipulation, manipulability
DOI: 10.3233/IFS-120733
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 253-257, 2014
Authors: Wei, Guiwu | Wang, Hongjun | Zhao, Xiaofei | Lin, Rui
Article Type: Research Article
Abstract: In this paper, we investigate the hesitant fuzzy multiple attribute decision making with incomplete weight information. An optimization model based on the maximizing deviation method, by which the attribute weights can be determined, is established. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We utilize the hesitant fuzzy weighted averaging (HFWA) operator to aggregate the hesitant fuzzy information corresponding to each alternative, and then rank the alternatives and select the …most desirable one (s) according to the score function. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. Show more
Keywords: Multiple attribute decision making, hesitant fuzzy information, hesitant fuzzy weighted averaging (HFWA) operator, weight information
DOI: 10.3233/IFS-120734
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 259-266, 2014
Authors: Wang, Shidong | He, Yaping | Zou, Ju Jia | Zhou, Dechuang | Wang, Jian
Article Type: Research Article
Abstract: A method of early smoke detection in video using swaying and diffusion feature is presented in this paper. Firstly, in view of early smoke's swaying feature, choquet fuzzy integral was adopted to extract dynamic regions from video frames, and then, a swaying identification algorithm based on centroid calculation was used to distinguish candidate smoke region from other dynamic regions. Secondly, smoke diffusion makes different textures between the bottom region and the top region of smoke. This unique feature was used to differentiate smoke from other candidate smoke regions by Gray Level Co-occurrence Matrix. Experiments show that the proposed method is …effective, robust, and has a performance of earlier smoke alarm. The processing rate of the smoke detection method achieves 25 frames per second with an image size of 320 × 240 pixels. Show more
Keywords: Smoke detection, choquet fuzzy integral, centroid, gray Level Co-occurrence Matrix
DOI: 10.3233/IFS-120735
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 267-275, 2014
Authors: Gunasekaran, M. | Ramaswami, K.S.
Article Type: Research Article
Abstract: This paper addresses about an approach that suggests for stock portfolio optimization using the combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Capital Asset Pricing Model (CAPM). Stock portfolio optimization aims to determine which of the stocks to be added to a portfolio based on the investor's needs, changing economic and market conditions. In order to construct an efficient prediction model, ANFIS is used to take decisions for forecasting the stock price using historical data of BSE SENSEX and well-known technical indicators. CAPM have been incorporated for portfolio optimization that can find the combination of stocks to offer an investor …trade-off between expected return and risk of a portfolio. ANFIS-CAPM plays a decisive role in discovering portfolio strategies for investors and creates the optimal portfolio from a combination of stocks. Experimental results show that the proposed hybrid intelligent system ANFIS-CAPM yields better performance than existing portfolio models. Show more
Keywords: Stock market forecasting, fuzzy logic, artificial neural network, portfolio optimization, Capital Asset Pricing Model (CAPM)
DOI: 10.3233/IFS-120736
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 277-286, 2014
Authors: Chou, Chien-Chang
Article Type: Research Article
Abstract: A new method for measuring the degree of similarity between fuzzy numbers is proposed in this paper. The advantage of the proposed method is to take account of the membership functions of fuzzy numbers while measuring the degree of similarity of fuzzy numbers. Finally, six sets of fuzzy numbers are used to compare the proposed method with the existing methods for similarity measure of fuzzy numbers. The results show that the proposed method for similarity measure seems to be more reasonable.
Keywords: Fuzzy sets theory, fuzzy number, similarity measure, membership function
DOI: 10.3233/IFS-120737
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 287-294, 2014
Authors: Aladag, Cagdas Hakan | Egrioglu, Erol | Yolcu, Ufufk | Uslu, Vedide R.
Article Type: Research Article
Abstract: There have been many recently proposed methods for forecasting fuzzy time series. Most of them are, however, for non-seasonal fuzzy time series. A definition of seasonal fuzzy time series was firstly given by Song (Q. Song, Seasonal forecasting in fuzzy time series, Fuzzy Sets and Systems 107 (1999), 235–236). In his paper, the model was a first order seasonal fuzzy time series. However, real time series behave very rarely in a first order seasonal fuzzy time series structure. There is a need for modeling high order seasonal structures because their structure generally is more complicated. We make a definition for …a high order seasonal fuzzy time series and propose a new approach based on artificial neural networks for forecasting a high order seasonal fuzzy time series. This proposed method is applied to the time series of the international tourism demand of Turkey. The results from this approach are compared to the results obtained from conventional seasonal fuzzy time series methods. From this comparisons we observe that the new method improve the forecasting accuracy. Show more
Keywords: Feed forward neural networks, forecasting, high order fuzzy time series, international tourism demand of Turkey, seasonal fuzzy time series
DOI: 10.3233/IFS-120738
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 295-302, 2014
Authors: Panić, Goran | Racković, Miloš | Škrbić, Srdan
Article Type: Research Article
Abstract: In real life, as opposed to virtual, most information comes in the form of imprecise or incomplete values. XML technology has made great progress in the field of storage and data transfer. We developed XML extension which combines indefiniteness in the values of XML and indefiniteness in the structure of XML into a single fuzzy XML extension. Furthermore, this paper expands XQuery syntax with fuzzy values and includes priorities and thresholds in fuzzy XQuery extension using GPFCSP for the first time. Unlike other papers that focus on setting up theories and defining syntax, in this paper, special attention is turned …to their practical use. A tool for working with XML, XSD and DTD documents and prioritized fuzzy XQuery extension queries has been developed. One of the advantages of this tool is defining arbitrary membership functions. The developed tool enables defined fuzzy XML extension and their performance to be tested in practice. Show more
Keywords: XML, XQuery, fuzzy logic
DOI: 10.3233/IFS-120739
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 303-316, 2014
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