this paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. finally an example is given to illustrate the performance of the methods.

A novel robust adaptive fuzzy control algorithm is presented for autonomous surface vehicle (ASV) autopilot. This paper studies an approach for fuzzy rule base optimization. The optimization solution especially solves the non-compatible problem in the generation process of fuzzy control rules. For the design study, the optimization model has been carried out in the simulink environment. It is s...

This paper exploits the ability of Symbiotic Evolution (SE), as a generic methodology, to elicit a fuzzy rule-base of the Mamdani-type. Almost all fuzzy rule-base generation algorithms produce rule-bases with redundant and overlapped membership functions that limit their interpretability elegance in their application. We address this problem by applying an algorithm to merge any similar members...

In this paper we introduce the content-based image classification using wavelet transform with Daubechies type 2 level 2 to process the characteristic texture consisting of standard deviation, mean and energy as Input variables, using the method of Fuzzy Neural Network (FNN). All the input value will be processed using fuzzyfication with 5 categories namely Very Low (VL), Low (L), Medium (M), H...

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only  considers both accuracy and generalization criteria in a single objective fu...

A special method for system modeling is presented to develop multi-variable fuzzy models on the basis of the system’s measured input and output data. The global modeling problem is proposed to be solved in two steps: by fuzzy model configuration and fuzzy model identification. The fuzzy model configuration procedure is characterized by preliminary considerations leading to the definition of the...

Fuzzy rule based systems provide a framework for representing & processing information in a way that resembles human communication & reasoning process. Two approaches can be found in the literature which is used for rule based generation; In Knowledge Driven Models the requisite rule base is provide by domain expert & knowledge engineers. In the Data Driven Models the rule base is generated fro...

This paper reviews some important points of sparse rule-bases, the reason of their generation and after that three methods are presented, which allow the approximation of the missing rules with reasonable demand on computing. The delimitations and advantages of these methods are presented, too. Fuzzy systems based on a sparse rule-base do not have rules for all the possible combinations of obse...

This paper reviews some important points of sparse rule-bases, the reason of their generation and after that three methods are presented, which allow the approximation of the missing rules with reasonable demand on computing. The delimitations and advantages of these methods are presented, too. Fuzzy systems based on a sparse rule-base do not have rules for all the possible combinations of obse...

The learning of a Fuzzy Rule-Based Classification System (FRBCS) by means of a supervised inductive process fundamentally implies four tasks that are complementary among them: the selection of the most informative variables to the classification problem to solve, the generation of a set of rules, the selection of the subset of rules with the best co-operation and the least redundancy, and the e...