Most approaches for the data-based design of fuzzy rule-based classi ers (e. g. [1{4]) require a manual de nition of membership functions (MBFs). In large applications, this task is very diÆcult and time-consuming for human experts. As a practical application, a possible scenario for a manual design of membership functions in a medical expert system to support gait analysis is demonstrated (Sec...

Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge. Since items may have their own characteristics, different minimum supports and membership functions may be specified for different items. In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions. In that paper,...

This paper proposes a new forecasting model based on the neural network with weighted fuzzy membership functions (NEWFM) concerning forecasting of turning points in the business cycle by the composite index. NEWFM is a new model of neural networks to improve forecasting accuracy by using self adaptive weighted fuzzy membership functions. The locations and weights of the membership functions are...

Ant Colony Systems (ACS) have been successfully applied to different optimization issues in recent years. However, only few works have been done by employing ACS method to data mining. This paper addresses the lack of investigations on this study by proposing an ACS -based algorithm to extract membership functions in fuzzy data mining. In this paper, the membership functions were encoded into b...

In almost every work on fuzzy sets, the existence of membership functions taking part in the considered model is assumed and it is not studied in depth whether or not such functions exist. On the other hand, generally the relationship between a certain studied characteristic and its referential set is not problematic since it is usually a matter of direct measurement. However, in a great variet...

A clonal selection algorithm (CLONALG) inspires from Clonal Selection Principle used to explain the basic features of an adaptive immune response to an antigenic stimulus. In this study, a new method is proposed for optimization of the Multiple Input Single Output (MISO) fuzzy membership functions using CLONALG. The most appropriate placement of membership functions with respect to fuzzy variab...

The subject of the study was hardware implementations of fuzzy controllers as CMOS analog devices on the base of implementation of fuzzy inference rules as multi-valued logic functions using summing amplifiers as building blocks. Earlier a functional completeness of summing amplifier with saturation in an arbitrary-valued logic was proven that gave a theoretical background for analog implementa...

The problem of deriving membership functions as a means for describing linguistic variables (for some control process) and the choice of fuzzy inference operators and connectives is at the heart of developing fuzzy control systems. Over the years con-nectionist systems have obtained prominence as a means to solve complicated learning tasks. More recently a surge in interest for applying neural ...

A set o f questionnaires was prepared to compare four elicitation methods: point esthnation, bzterval estflnation, membership function exemplification, and pairwise comparison. Technical and nontechnical topics were involved, assuming subjects performed either as measurenlent instruments or as repositories o f knowledge. The advantages, disadvantages, and limitations of each method are discusse...