An approach is developed to MR brain images segmentation, based on pixel classification using Fuzzy Rule Based system and Fuzzy Similarity measures. The cerebral images are segmented into gray matter, white matter, and cerebrospinal fluid (CSF). Image preprocessing was first done to improve the quality of brain MR images and reducing artifacts. The feature vector was selected to be the pixel an...

Few replies get published. Many that do get published could be more effective. A reply can be effective only if it is published, readable, and credible. This article suggests guidelines for writing good replies. The guidelines begin with things to keep in mind—for example, that you might be wrong—and things to do before you begin to write. The latter include considering not responding, consider...

This paper presents an algorithm to extract rules relating input/output data and including prior knowledge. The rules are created in the environment of fuzzy systems. The fuzzy sets describing the system are constructed within a framework of linguistic integrity to guarantee its interpretability in the linguistic context. Two algorithms are presented in this paper. The main algorithm is the aut...

Development of a neural-fuzzy model for an operational hydrocyclone is reported in this paper. The model integrates the benefits of the Artijkial Neural Network (ANN) and the fuzzy-logic techniques. It preserves the generalisation capability of an ANN while expressing the final model in fuzzy rules. These rules can be modiJied and examined by the user. This will in turn control the interpretati...

The paper focuses on the application of neuro-fuzzy techniques in fault detection and isolation. The objective of this paper is to detect and isolate faults to an industrial gas turbine, with emphasis on faults occurred in the actuator part of the gas turbine. A neuro-fuzzy based learning and adaptation of TSK fuzzy models is used for residual generation, while for residual evaluation a neuro-f...

An Evolutionary Algorithm (EA) strategy for the optimization of generic Work-In-Process (WIP) scheduling fuzzy controllers is presented. The EA is used to tune a set of fuzzy control modules which are used for distributed and supervisory WIP scheduling. The distributed controllers objective is to control the rate in each production stage so that satisfies the demand for final products while red...

This chapter gives insight in the use of Genetic-Based Machine Learning (GBML) for supervised tasks. Five GBML systems which represent different learning methodologies and knowledge representations in the GBML paradigm are selected for the analysis: UCS, GAssist, SLAVE, Fuzzy AdaBoost, and Fuzzy LogitBoost. UCS and GAssist are based on a non-fuzzy representation, while SLAVE, Fuzzy AdaBoost, an...

System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused o...

The notion of fuzzy sets 6 relates to objects with unsharp boundaries and the degrees of membership plays a crucial role in describing them. In case of fuzzy sets, we allow the truths of propositions to be expressed in terms of degrees which offers a considerably broader framework for knowledge representation while dealing with uncertainty. In his paper , Heilpern introduced the concept of a fu...

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function ...