Journal of Intelligent & Fuzzy Systems - Volume 2, issue 3

Authors: Yager, Ronald R. | Filev, Dimitar P.

Article Type: Research Article

Abstract: We develop, based upon the mountain clustering method, a procedure for learning fuzzy systems models from data. First we discuss the mountain clustering method. We then show how it could be used to obtain the structure of fuzzy systems models. The initial estimates of this model are obtained from the cluster centers. We then use a back propagation algorithm to tune the model.

DOI: 10.3233/IFS-1994-2301

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 209-219, 1994

Authors: Gardella, S. | Kumagai, T. | Hashimoto, R. | Wada, M.

Article Type: Research Article

Abstract: A model of a fully interconnected neural network composed of neurons having a refractory period and integrating the afferent signals is presented. A theoretical analysis of its dynamics is carried out, considering the general case with periodic input and output sequences from which a teaching algorithm for storing periodic sequences in the network is derived. Finally, the performances of the network are illustrated through a selected example and its potentialities, as well as its possible applications, are discussed.

DOI: 10.3233/IFS-1994-2302

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 221-228, 1994

Authors: Hogans IV, John E. | Homaifar, Abdollah | Sayyarrodsari, Bijan

Article Type: Research Article

Abstract: Today's technology requires controls capable of handling highly nonlinear, time-varying, uncertain systems. Variable structure control (VSC) is one such control method. Variable structure control is invariant to system perturbations and external disturbances; however, a high-frequency control chattering exists that renders the VSC impractical for most applications. Fuzzy inference can be used to reduce the chattering. By using fuzzy inference to determine the switching scheme of the VSC, the original robustness and fast response time of the VSC can be retained while reducing the control chattering. Optimization of the fuzzy parameters using genetic algorithms will also produce a system with improved …response time and accuracy. Show more

DOI: 10.3233/IFS-1994-2303

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 229-241, 1994

Authors: Lin, Yinghua | Cunningham III, George A.

Article Type: Research Article

Abstract: We propose a new neural network for implementing fuzzy systems, and we prove that it can represent any continuous function over a compact set. We propose and test a method for building a fuzzy neural system from input-output data. We analyze the output data using fuzzy c-means to obtain the number of rules and to set some of the initial weights in the network. Then, we use this fuzzy neural network to identify the input variables and to determine the number of input membership functions. We show that the resulting model is simpler and yields better performance than previously proposed …methods for extracting fuzzy systems and neural networks from input-output data. Show more

DOI: 10.3233/IFS-1994-2304

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 243-250, 1994

Authors: Adams, Teresa M.

Article Type: Research Article

Abstract: Multiobjective decisions are frequently required for planning and managing highway construction projects. One example is the selection of an earth retaining structure. This article presents a case-by-case comparison of two multiobjective decision methods for selecting a retaining wall type from a set of possible alternatives given a finite set of selection criteria of concern to the decision maker. The first method is a weighting technique. The second method is based on fuzzy logic. The methods are compared according to agreement of outcome, sensitivity to changes in the importance of the selection criteria, and sensitivity to changes in the degree to …which each alternative satisfies the criteria. Results indicate superior performance of the fuzzy method for retaining wall selection. Show more

DOI: 10.3233/IFS-1994-2305

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 251-265, 1994

Authors: Chiu, Stephen L.

Article Type: Research Article

Abstract: We present an efficient method for estimating cluster centers of numerical data. This method can be used to determine the number of clusters and their initial values for initializing iterative optimization-based clustering algorithms such as fuzzy C-means. Here we use the cluster estimation method as the basis of a fast and robust algorithm for identifying fuzzy models. A benchmark problem involving the prediction of a chaotic time series shows this model identification method compares favorably with other, more computationally intensive methods. We also illustrate an application of this method in modeling the relationship between automobile trips and demographic factors.

DOI: 10.3233/IFS-1994-2306

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 267-278, 1994

Authors: Kim, Kwang-Choon | Kim, Jong-Hwan

Article Type: Research Article

Abstract: In this article, we propose a multicriteria fuzzy control (MFC) based on fuzzy measures and fuzzy integrals. The basic idea underlying this approach is based on analyzing the source of attributes of the system output response and applying the fuzzy measure and integral theory to the existing fuzzy control. With this scheme, we can tune the three attributes of rise time, overshoot, and settling time of the output response. We demonstrate that MFC has excellent control performance compared to conventional fuzzy control by computer simulations as well as via experiments performed on a DC servomotor angular position control. Moreover, our …scheme can be easily implemented in practice simply by adding weight terms to existing fuzzy rules and assigning the weight to each rule by employing the fuzzy measure and integral. Show more

DOI: 10.3233/IFS-1994-2307

Citation: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 3, pp. 279-288, 1994