Journal of Intelligent & Fuzzy Systems - Volume 18, issue 1

Authors: de Sá Lisboa, Flávia O. Santos | do Carmo Nicoletti, Maria | Ramer, Arthur

Article Type: Research Article

Abstract: The Nested Generalized Exemplar (NGE) model is an incremental form of inductive learning that generalizes a given training set into hypotheses represented as a set of hyperrectangles in an n-dimensional Euclidean space. The NGE algorithm can be considered a descendent of either Nearest Neighbor (NN) or K-Nearest Neighbor (KNN) algorithms. NGE based systems classify new instances by calculating their similarity to the nearest generalized exemplar (i.e. hyperrectangle). Similarity in an NGE model is implemented by a …distance metric namely the Euclidean distance. This paper describes a version of the NGE model suitable for fuzzy domains called Fuzzy NGE (F-NGE). F-NGE learns fuzzy rules for classifying instances into crisp classes. An implementation of F-NGE has been tested in several different knowledge domains for which results are presented and discussed. Results of fuzzy versions of NN and KNN using the same domains are also presented, for comparison. Show more

Keywords: NGE, NN, KNN, Fuzzy NGE

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 1-17, 2007

Authors: Wu, Sheng-Ming | Sun, Chein-Chung | Chung, Hung-Yuan | Chang, Wen-Jer

Article Type: Research Article

Abstract: In this paper, Takagi-Sugeno (T-S) fuzzy control problem with minimizing H_2 /H_&infty; norm is studied. A new approach in designing fuzzy controller is called T-S region-based fuzzy controller (TSRFC), which is derived from the fuzzy region concept and the robust control technique. The fuzzy region concept is used to divide the general plant rules into several fuzzy regions and the robust control technique is used to stabilize all plant rules of each fuzzy …region. A theorem in synthesizing TSRFC is derived from Lyapunov stability criterion, which is expressed in terms of LMIs. This proposed idea is greatly reduced the total number of LMIs and controller rules. For this reason, TSRFC is easy to implement with simple hardware. TSRFC is able to provide good performances as well as PDC-based designs even though the controller rules are reduced. Show more

Keywords: Takagi-Sugeno fuzzy systems, Fuzzy region concept, Linear Matrix Inequality (LMI) and H_2/H_&infty; control

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 19-30, 2007

Authors: Oh, Sung-Kwun | Pedrycz, Witold | Park, Keon-Jun

Article Type: Research Article

Abstract: In this study, we introduce a new category of fuzzy inference systems based on data (information) granulation and show their applications to the identification of complex and usually nonlinear systems. Information granules are treated as collections of objects (data, in particular) brought together by the criteria of proximity, similarity, or functionality. The formal framework of information granulation along with the information granules themselves become an important design feature of fuzzy models, which in essence …are geared towards capturing relationship between information granules rather than plain numeric data. The key characteristics of experimental data being used in the construction of the fuzzy model are carefully reflected by fuzzy rules formed therein. Information granulation realized with the aid of Hard C-Means (HCM) clustering helps determine the initial values of the parameters of the fuzzy models. This in particular concerns such important components of the rules as the initial apexes of the membership functions standing in the premise part of the fuzzy rules and the initial values of the polynomial functions present in their consequence part. The initial values of the parameters are tuned effectively with the aid of the genetic algorithms (GAs) and the least square method (LSM). An aggregate objective function is constructed in order to strike a sound balance between the approximation and generalization capabilities of the fuzzy model. The model is evaluated with the use of numerical experimentation and contrasted with the quality of some "conventional" fuzzy models already encountered in the literature. Show more

Keywords: Information Granulation (IG), Fuzzy Inference System (FIS), Genetic Algorithms (GAs), Hard C-Means (HCM) clustering, least square method, design procedure

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 31-41, 2007

Authors: Lee, S.H. | Howlett, R.J. | Crua, C. | Walters, S.D.

Article Type: Research Article

Abstract: The aim of this study was to demonstrate the effectiveness of an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of diesel spray penetration length in the cylinder of a diesel internal combustion engine. The technique involved extraction of necessary representative features from a collection of raw image data. A comparative evaluation of two fuzzy-derived techniques for modelling fuel spray penetration is described. The first model was implemented using a conventional fuzzy-based paradigm, where …human expertise and operator knowledge were used to select the parameters for the system. The second model used an adaptive neuro-fuzzy inference system (ANFIS), where automatic adjustment of the system parameters was effected by a neural network based on prior knowledge. Two engine operating parameters were used as inputs to the model; namely in-cylinder pressure and air density. Spray penetration length was modelled on the basis of these two inputs. The models derived using the two techniques were validated using test data that had not been used during training. The ANFIS model was shown to achieve an improved accuracy compared to a pure fuzzy model, based on conveniently selected parameters. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 43-56, 2007

Authors: Zarandi, M.H. Fazel | Turksen, I.B. | Hadian, S.M.

Article Type: Research Article

Abstract: In this paper, we propose an indirect method to fuzzy modeling which implements a clustering algorithm to build a linguistic fuzzy controller. Based on output data clustering and projection onto the input spaces, the number of clusters is determined and rules are generated automatically. A new methodology based on output sensitivity is developed for input variable selection. Then, implementing an Adapted Neural Network for the selection of membership functions optimizes all membership function parameters. The unbounded …parameters of fuzzy operators and the inference methods of FATI (First Aggregate, Then Infer) and FITA (First Infer, Then Aggregate) are optimized through a simple and efficient tuning strategy. Show more

Keywords: Fuzzy clustering, variable selection, parameter identification, inference method, tuning, fuzzy control, steam generation plant

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 57-71, 2007

Authors: Kim, Sunhyo | Oh, Se-Young

Article Type: Research Article

Abstract: Visual servoing requires the target object to be in the field of view of the camera all the time. At the same time, we also want to achieve optimal path planning and controllability of the robot pose. This paper presents a new hybrid fuzzy control method for visual servoing of mobile robots to meet these requirements. IBVS (Image Based Visual Servoing) calculates the motion plan directly from the image space using the inverse image Jacobian so …that the target object always stays within the field of view. In contrast, PBVS (Position Based Visual Servoing) uses an image-to-work space transform to plan an optimal pose trajectory directly in the cartesian. The proposed fuzzy control then integrates these two types of visual servoing through a warning signal indicating the target may escape the field of view. Also, we use the neural network for the prediction of the target position for a robust timely tracking of the object. Simulation and real experimental work based on MORIS, our mobile robot test bed, verify the efficacy of this approach. Show more

Keywords: Image based visual servoing, position based visual servoing, mobile robotics, fuzzy system, neural network

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 73-82, 2007

Authors: Lu, Jie | Wu, Fengjie | Zhang, Guangquan

Article Type: Research Article

Abstract: Many organizational decision problems can be formulated by multi-objective linear programming (MOLP) models. Referring to the imprecision inherent in human judgments, uncertainty may be incorporated in the parameters of an MOLP model when it is established, which is called a Fuzzy MOLP (FMOLP) problem. What is an optimal solution for an FMOLP problem is the first issue to deal with in this study. The second issue is how to effectively derive an optimal solution for an …FMOLP problem since uncertainty is also reflected in a solution process of an FMOLP problem. By introducing three types of comparison of fuzzy numbers and an adjustable satisfactory degree α in this study, a new solution concept of FMOLP is given. For handling the second issue, this study develops an interactive fuzzy goal optimization method which provides an interactive fashion with decision makers during their solution process and allows decision makers to give their fuzzy goals in any forms of membership functions. An illustrative example gives the details of the solution concept and the proposed method. Show more

Keywords: Optimization, fuzzy programming, multi-objective linear programming, interactive decision-making method

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 83-97, 2007

Authors: Ghazinoory, S. | Esmail Zadeh, A. | Memariani, A.

Article Type: Research Article

Abstract: The SWOT (which is sometimes called TOWS) matrix is one of the most important tools for strategic planning specially in the stage of extracting strategies. While the use of SWOT is quite common and popular, it still continues to have certain structural problems. The most important of which are the lack of considering uncertain and two sided factors, lack of prioritization of the factors and strategies and too many extractable strategies. This paper attempts to solve …some of the problems by following the fuzzy approach to the internal and external factors (in the form of fuzzy membership functions). The presented algorithm in this article prioritizes and extracts the most significant strategies based on the intensity of the effect. Show more

Keywords: Fuzzy, SWOT, strategic planning

Citation: Journal of Intelligent & Fuzzy Systems, vol. 18, no. 1, pp. 99-108, 2007