Some difficulties emerging during the construction of fuzzy rule bases are inherited from the type of the applied fuzzy reasoning. The fuzzy rule base requested for many classical reasoning methods needed to be complete. In case of fetching fuzzy rules directly from expert knowledge, the way of building a complete rule base is not always straightforward. One simple solution for overcoming the n...

Fact Gathering means generating rule base from available numerical data or data base. The intelligence of a fuzzy system lies in its rule base. Generating rule base is one of the most important and difficult tasks when designing fuzzy systems. Various rule base generation methods are used such as Neural networks, genetic algorithms, biogeography based optimization approach, ant colony optimizat...

Economic modeling of financial markets attempts to model highly complex systems in which expectations can be among the dominant driving forces. It is necessary, then, to focus on how agents form expectations. We believe that they look for patterns, hypothesize, try, make mistakes, learn and adapt. Agents’ bounded rationality leads us to a rule-based approach which we model using Fuzzy Rule Base...

Economic modelling of financial markets means to model highly complex systems in which expectations can be the dominant driving forces. Therefore it is necessary to focus on how agents form their expectations. We believe that they look for patterns, hypothesize, try, make mistakes, learn and adapt. Agents’ bounded rationality leads us to a rule-based approach which we model using Fuzzy Rule-Bas...

The proposed method develops a fuzzy rule-based classifier that was tested using features for islanding detection in distributed generation. In the developed technique, the initial classification boundaries are found out by using the decision tree (DT). From the DT classification boundaries, the fuzzy membership functions (MFs) are developed and the corresponding rule base is formulated for isl...

We provide a way to combine matrix Lyapunov systems with fuzzy rules to form a new fuzzy system called fuzzy dynamical matrix Lyapunov system, which can be regarded as a new approach to intelligent control. First, we study the controllability property of the fuzzy dynamical matrix Lyapunov system and provide a sufficient condition for its controllability with the use of fuzzy rule base. The sig...

A rule base reduction and tuning algorithm is proposed as a design tool for the knowledge-based fuzzy control of a vacuum cleaner. Given a set of expert-based control rules in a fuzzy rule base structure, proposed algorithm computes the inconsistencies and redundancies in the overall rule set based on a newly proposed measure of equality of the individual fuzzy sets. An inconsistency and redund...

This paper presents a layer-structured fuzzy neural network (FNN) for learning rules of fuzzy-logic control systems. Initially, FNN is constructed to contain all the possible fuzzy rules. We propose a two-phase learning procedure for this network. The first phase is a error-backprop (EBP) training, and the second phase is a rule pruning. Since some functions of the nodes in the FNN have the com...