Journal of Intelligent & Fuzzy Systems - Volume 11, issue 3-4

Authors: Alcalá, Rafael | Casillas, Jorge | Cordón, Oscar | Herrera, Francisco

Article Type: Research Article

Abstract: The use of Mamdani-type fuzzy rule-based systems (FRBSs) allows us to deal with the modeling of systems building a linguistic model clearly interpretable by human beings. However, the accuracy obtained is not sometimes as good as desired. This fact relates to the restriction imposed when using linguistic variables, which forces the membership functions considered in each fuzzy linguistic rule to belong to a common set of them, i.e., to use a global grid. To solve this …problem, in the last few years a new variant has been proposed working directly with fuzzy variables in the fuzzy rules instead of linguistic terms, thus ignoring the said restriction. Therefore, these systems, which are totally equivalent to fuzzy graphs (defined by Zadeh as granular representations of functional dependencies and relations), do not consider a global grid and could be named {\it non-grid-oriented} (NGO) FRBSs. Of course, the main objective of these models is the accuracy of the system instead its interpretability. Until now, NGO FRBSs have been little considered and developed in the literature. However, and due to their good accuracy, their use is increasing thus making necessary a wide analysis on the features and associated learning methods in the NGO domain. This contribution aims at analyzing the structure and framework of NGO FRBSs, as well as making a taxonomy of learning methods considering the constrains imposed on the fuzzy sets in the generation process. Some automatic learning techniques and methods proposed in the literature to build these fuzzy graphs will be also reviewed and analyzed when solving several applications of different nature. Show more

Keywords: fuzzy graphs, fuzzy modeling, non-grid-oriented fuzzy rule-based systems, accuracy improvement, learning

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 99-119, 2001

Authors: Jarrah, M.A. | Shaout, A.

Article Type: Research Article

Abstract: An autonomous intelligent cruise control system was designed and simulated based on measured relative distance, speed, and acceleration. These constitute the fuzzy inputs. The results have shown that the system can be robust to noisy distance measurements and modular in structure to ease its implementation. A simple way of estimating the road condition was developed, implemented and tested in simulation. The results show that based on the measured relationship between the deceleration and brake pressure, the …brake pressure output gain can be adjusted to prevent lock up of the tires and the consequent loss of stability. Two controller implementations were tested. The first one is based on heuristic knowledge of the system using Mamdani inference system. The second model was based on offline adaptive neuro-fuzzy controller model. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 121-134, 2001

Authors: Yoon, Jeong-Mi | de Korvin, André

Article Type: Research Article

Abstract: To decide on an optimal pain medicine from a clinician's viewpoint for patients who complain about pain after surgery, we use the method of Analytical Hierarchical Processes (AHP). This is an extended application of the classical AHP which has optimality. Uncertainty in assigning priorities and the use of semantic variables leads to the inclusion of fuzzy sets into the structure of the AHP paradigm. We describe our model by a hierarchical process having four levels. We …will introduce inconsistencies in some of our evaluations. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 135-145, 2001

Authors: Paiva, Rui Pedro | Dourado, António

Article Type: Research Article

Abstract: A methodology and experimental comparison of neuro-fuzzy structures, namely linguistic and zero and first-order Takagi-Sugeno, are developed. The implementation of the model is conducted through the training of a neuro-fuzzy network, i.e., a neural net architecture capable of representing a fuzzy system. In the first phase, the structure of the model is obtained by subtractive clustering, which allows the extraction of a set of relevant rules based on a set of representative input-output data samples. Membership …functions with two-sided Gaussian functions are proposed and discussed. In the second phase, the model parameters are tuned via the training of a neural network. Furthermore, different fuzzy operators are compared, as well as regular and two-sided Gaussian functions. Show more

Keywords: neuro-fuzzy systems, structure learning, parameter learning, clustering

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 147-161, 2001

Authors: Zhang, Runtong | Phillis, Yannis A.

Article Type: Research Article

Abstract: We consider a queueing system with two parallel heterogeneous servers. Each exponential server has its own queue and customers arrive at each queue according to independent Poisson processes. When a customer arrives at queue 1, the customer can be transferred to queue 2 by paying an assignment cost. Each customer in queue pays a holding cost per unit time. The objective is to dynamically determine the optimal assignment policy, based on the state of the system, …so as to minimize the average cost. In this paper, a novel approach is presented using fuzzy control to solve the problem. Simulation shows that the approach is efficient and promising. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 163-169, 2001

Authors: Al-Jarrah, Omar M. | Bani-Melhem, Omar Q.

Article Type: Research Article

Abstract: For a mobile robot to navigate in a completely unknown environment, it has to perceive its environment locally or globally, reason about its perceptions, and act accordingly. This paper presents a method for building environmental maps for mobile robot navigation using fuzzy classification of ultrasonic range data. The paper concentrates on the classification method. A fuzzy classifier is built to classify the ultrasonic data while the robot is exploring its environment. The generated map will be …a graph-representation (topological) of the environment in which nodes represent situation areas and edges represent transitions between these areas. The fuzzy classification is compared with self-organizing feature map neural network classifier. It is shown that when using fuzzy classification, the generated nodes in the map are reduced. This will reduce the time to build the path between the start and target positions. Simulation results prove the success of the fuzzy classification in building environmental maps in comparison with neural networks. Show more

Keywords: fuzzy, classification, navigation, mobile robot, topological map, ultra-sonic sensors

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 171-184, 2001

Authors: Rahim, A.H.M.A. | Al-Maghraby, H.M. | Nowicki, E.P.

Article Type: Research Article

Abstract: Static VAR compensators (SVC) are known to improve voltage and reactive power flow in a power system. Properly controlled SVCs can also provide damping to power system oscillations. This article presents a fuzzy logic SVC controller design for damping control considering different input signals. A fuzzy logic control strategy has been developed that uses crisp optimum control theory to obtain the best combination of speed deviation and acceleration signals so as to stabilize the system in …minimum time. The proposed fuzzy controller requires much less fuzzy variables, and is computationally very efficient. Simulation results show that the crisp optimum control based fuzzy logic controller provides excellent damping to the power system compared to the general fuzzy strategies. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 11, no. 3-4, pp. 185-194, 2001