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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: Yan, Hong-Sen | Jiang, Tian-Hua | Shi, Wen-Wu | Li, Shan
Article Type: Research Article
Abstract: Proposed in this paper is a new economic production lot size (EPLS) model, i.e., a multi-cycle flexible production/inventory model under random demands, which considers the holding and shortage costs of finished products as well as the setup costs of production, and employs an (s,Q) policy for production/inventory control. We have theoretically proved that the total expected cost of the model is a convex function with respect to variables s and Q. On this basis, an iterative learning algorithm is designed to speed up the process by using the model convexity, which enables us to obtain the optimal production preparation point …and the optimal production quantity. Results from the comparison between the proposed algorithm and the genetic algorithm (GA) show that the control quantities secured by the two algorithms are consistent but the former has higher solution speed, which verifies the accuracy and effectiveness of the proposed model and algorithm. Show more
Keywords: Production/inventory control, economic production lot size, iterative learning, random demand
DOI: 10.3233/IFS-130930
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2591-2607, 2014
Authors: Yan, Li | Wang, Hailong | Ma, Z.M.
Article Type: Research Article
Abstract: It is widely recognized that management of data types is an indispensable component in intelligent knowledge-based applications. Recent research has shown that OWL (Web Ontology Language) has a serious limitation on data types and does not support customized data types and predicates. Some work has been carried out to address this issue in crisp situations. In order to deal with fuzzy information in the Semantic Web, this paper proposes a new kind of fuzzy description logic F-SHIQ(G), which can support not only the representation and reasoning of fuzzy concept knowledge, but also fuzzy data information with customized fuzzy data types …and customized fuzzy data type predicates. The syntax, semantics and reasoning algorithm of the F-SHIQ(G) are investigated in the paper, and its decidability, soundness, completeness and complexity of the reasoning algorithm are discussed in the paper also. For the reasoning for F-SHIQ(G), the paper adopts a traditional reasoning architecture for fuzzy data type reasoning and as a result, new fuzzy data type reasoners can be added without changing the fuzzy concept reasoner. Show more
Keywords: Fuzzy description logic, F-SHIQ(G), reasoning architecture, customized fuzzy data type, reasoning complexity
DOI: 10.3233/IFS-130931
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2609-2626, 2014
Authors: Yolcu, Ufuk | Cagcag, Ozge | Aladag, Cagdas Hakan | Egrioglu, Erol
Article Type: Research Article
Abstract: In recent years, several forecasting methods have been proposed for the analysis of fuzzy time series. Determination of fuzzy relations and establishing interval lengths, which is used in partition of universe of discourse, can be considered as the two of main elements affecting the forecasting performance of these forecasting methods. In the literature, along with the studies in which interval lengths are determined subjectively, algorithms such as genetic algorithms and particle swarm optimization have been utilized. In this study, a new fuzzy time series forecasting method which uses Artificial Bee Colony (ABC) algorithm for the determination of interval lengths for …the first time in the literature is proposed. To obtain forecasts, this new method makes use of fuzzy logic relationship tables in determining the fuzzy relations and also uses estimating based on next state (EBN) for training set and master voting (MV) scheme for test set. The new proposed method is applied to three various time series and when compared with the existing methods better results are obtained with regard to both training and test set. Show more
Keywords: Artificial bee colony, forecasting, fuzzy time series, fuzzification
DOI: 10.3233/IFS-130933
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2627-2637, 2014
Authors: Li, Qingxiang | Zhao, Xiaofei | Wei, Guiwu
Article Type: Research Article
Abstract: In this paper, we investigate the multiple attribute decision making (MADM) problem for software quality evaluation based on the geometric aggregation operators with hesitant fuzzy uncertain linguistic information. Then, motivated by the ideal of traditional geometric operation, we have developed some geometric aggregation operators for aggregating hesitant fuzzy uncertain linguistic information. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the hesitant fuzzy uncertain linguistic multiple attribute decision making problems. Finally, a practical example for software quality evaluation is given to verify the developed approach and to demonstrate …its practicality and effectiveness. Show more
Keywords: Multiple attribute decision making (MADM), hesitant fuzzy uncertain linguistic values, hesitant fuzzy uncertain linguistic geometric aggregation operators, software quality evaluation
DOI: 10.3233/IFS-130934
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2639-2647, 2014
Authors: Fazel Zarandi, Mohammad Hossein | Hemmati, Ahmad | Davari, Soheil | Turksen, I. Burhan
Article Type: Research Article
Abstract: This paper puts forward a location-routing problem with fuzzy demands (LRPFD). A fuzzy chance constrained programming (CCP) model is presented and a simulation-embedded simulated annealing (SA) algorithm is proposed to solve it. Moreover, an initialization heuristic is presented which is based on the well-known fuzzy c-means clustering algorithm. Numerical examples clearly show the effectiveness of the proposed solution procedure. In addition, the sensitivity analysis of the objective function based on the dispatcher preference index is presented.
Keywords: Location-routing problem (LRP), uncertainty, fuzzy logic, simulation, simulated annealing, credibility theory
DOI: 10.3233/IFS-130935
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2649-2660, 2014
Authors: Nemissi, M. | Seridi, H. | Akdag, H.
Article Type: Research Article
Abstract: This paper introduces a neuro-fuzzy framework for handling multi-class classification problems. Instead of decomposing such problems into simple sub-problems and solving each part using a different classifier, the proposed system decomposes and implements the entire problem automatically in the same framework. The decomposition is performed using the most commonly used methods for dividing multi-class classification problems: OAA (one-against-all) and OAO (one-against-one). Consequently, two models are introduced: OAA and OAO based neuro-fuzzy classifiers. The design of the proposed models is based on the implementation of each sub-problem using a set of weights. The learning is performed by adjusting every set independently, …and without adjusting the parameters of membership functions. This considerably simplifies the classification and learning tasks. After the learning stage, the proposed systems act as a single-module classifier for recognizing new examples. Show more
Keywords: Pattern recognition, machine learning, multi-class classification, neuro-fuzzy systems
DOI: 10.3233/IFS-130936
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2661-2670, 2014
Authors: Nandi, Arup Kumar
Article Type: Research Article
Abstract: In the present work, an extensive experimental study on the equivalent hardness of various particle reinforced flexible mould materials is carried out. From the experimental study, it has been observed that the equivalent hardness of a composite mould material depend on many factors, such as filler content, morphology and type of filler particles, etc. Some of the factors may be correlated with each other and sometimes belong to uncertainty and ambiguity such as dispersion state of filler in the matrix, non-uniform filler particle size and shape. Moreover, the formation of physical bonding of filler particles with matrix polymer is highly …complex and non-linear, because they are depending on such kind of parameters that are associated with uncertainty and ambiguity. By realizing it, an effort has been made to develop a model using a GA-fuzzy approach to estimate equivalent hardness of particle reinforced mould materials. An appropriate model is decided by carrying out a comparative analysis on the effectiveness of developed models based on different structures of TSK-type fuzzy rule-consequent function with the experimental measurements. It is found that better performance is envisaged by TSK-type fuzzy model which considers the variables namely hardness of polymer, hardness of filler material, volume fraction of filler particle as well as interactions among them in the rule-consequent function. In addition, the developed model seems to possess a generic one which can be applicable to a wide range of two-phase particle-reinforced composite mould materials. Show more
Keywords: GA-fuzzy approach, equivalent hardness, particle reinforced composite mould material, soft tooling process
DOI: 10.3233/IFS-130937
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2671-2683, 2014
Authors: Çanak, İbrahim
Article Type: Research Article
Abstract: We state and prove a fuzzy analogue of a Theorem due to Móricz and Rhoades [Acta Math. Hungar. 102 (4) (2004), 279–285].
Keywords: Riesz mean, fuzzy real number, fuzzy sequences, Tauberian conditions
DOI: 10.3233/IFS-130938
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2685-2688, 2014
Authors: Zhou, Liyong | Zhao, Xiaofei | Wei, Guiwu
Article Type: Research Article
Abstract: Hamacher product is a t-norm and Hamacher sum is a t-conorm. They are good alternatives to algebraic product and algebraic sum, respectively. Nevertheless, it seems that most of the existing hesitant fuzzy aggregation operators are based on the algebraic operations. In this paper, we utilize Hamacher operations to develop some hesitant fuzzy aggregation operators. Then, we have utilized these operators to develop some approaches to solve the hesitant fuzzy multiple attribute decision making problems. Finally, a practical example for evaluating the customer satisfaction of e-commerce websites is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords: Multiple attribute decision making (MADM), hesitant fuzzy values, Hamacher aggregation operators, hesitant fuzzy Hamacher hybrid average (HFHHA) operator, customer satisfaction, e-commerce websites
DOI: 10.3233/IFS-130939
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2689-2699, 2014
Authors: Vu, Ho | Hoa, Ngo Van | Phu, Nguyen Dinh
Article Type: Research Article
Abstract: In this paper, we consider the random fuzzy integro-differential equations (RFIDEs) under generalized H-differentiability. The local existence of solutions for RFIDEs with initial conditions under generalized H-differentiability is studied. Two theorems for local existence of solutions are given and proved. Some examples are given to illustrate these results.
Keywords: Random fuzzy, random fuzzy differential equations, random fuzzy integro-differential equations, generalized Hukuhara derivative
DOI: 10.3233/IFS-130940
Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2701-2717, 2014
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