No abstract

In this paper, we propose automatic generation methods of fuzzy classification rules with the Genetic Algorithms (GAs) to obtain compact fuzzy systems. This time, we propose an approach of hyper-cone membership function to construct rules for the antecedent part. Then, this method is determined the location and shape of hyper-cone membership function in the antecedent part, output class and the number of necessary inputs of each rule by GAs. Also, using the rule addition method in GA process, compact fuzzy classification systems are obtained. Though the proposed methods are quite simple, the process of GAs on both methods presents a solving for two-objective optimization problems: increasing the numbers of correct pattern classification, while decreasing the rule and input numbers optimally. This method was applied to Wine data sets and Wisconsin Prognostic Breast Cancer (WPBC) data sets. Wine data sets consist of 13 inputs and three outputs, while WPBC data sets contain 33 inputs and two outputs.

Thb paper proposes a fuzy ckss&r system (FCS) wing ri-y r u l e given by hypercone memhsrahlp funetloar. Tbe hyper-mne membership h c t i o n k expressed by a kind of radial basis funtlon, and ita fuzy rules m be flexibly located in input and output spa-.Therefore, The FCSgenerate excellent rule which beve the best loation and shape of memberablp bctloras. We apply the FCS to a fuzzy rule generation for the inverted pendulum control. A h , we introduce the simplified r e d acquisition method for evaluation of inverted pendulum performaoce.

(Hokuriku Gakuen) and Hiroyuki Inoue, Non-member (Fukui University) This paper describes the environmental learning support system with Collaborative Learning. The learning support system is used with the client system, which chat data of student is corresponded with the server system using computer network.

This paper describes the cartographic information processing system using verbal representation. The verbal representation is a new method for representing the multi-dimensional surfaces, which human beings use for representing of topography. This method has not only advantages of representing relationship between mountains and valleys, but allows one to form a concept of shapes through a little bit of information because the relationship is represented by labels(or words).In this paper, the words used for the verbal representation are defined in 3D space. Next, the outline of the cartographic information processing system is described. The system has two subsystems, which are shape representing subsystem and shape recognizing subsystem of topography. Each subsystem constructed some units. Finally, the recognizing process of the topography at the shape recognizing subsystem is shown.