This paper examines the effect of rule weights in fuzzy rule-based classification systems. Each fuzzy IF–THEN rule in our classification system has antecedent linguistic values and a single consequent class. We use a fuzzy reasoning method based on a single winner rule in the classification phase. The winner rule for a new pattern is the fuzzy IF–THEN rule that has the maximum compatibility gra...

Agent based models of human systems, such as those found in behavioural economics, implement their agents intelligence through the use of simple rules. These models have proved to be worthwhile research tools. However, improving the outputs of these models will require a greater emphasis on the development of intelligence within the model agents. A deeper understanding of the cognitive process ...

A novel fuzzy-logic-based control for vehicle-active suspension is suggested. The vehicle vibration and disturbance are reduced considerably with a fuzzy logic controller, to enhance comfort in riding faced with uncertain road terrains. A quarter-car active suspension system is controlled to reduce the vertical acceleration to a level of, that of, a hypothetical reference model. A new look-up t...

Mamdani controller was successfully used in many applications. One of its interpretations is that it uses a fuzzy relation as an approximation of the desirable input–output correspondence. We analyze mathematical properties of Mamdani controller and notice that it has lower computational complexity when compared to the residuum-based controller. However, we show that in standard situations, bot...

Fuzzy rule-based systems have been very popular in many engineering applications. In mineral engineering, fuzzy rules are normally constructed using some fuzzy rule extraction techniques to establish the determination model in predicting the d50c of hydrocyclones. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. The use of more than...

This paper deals with the influence of the context in fuzzy rule base systems. The linguistic variable definition of Zadeh is modified to permit context adaptation, and inference procedure is modified to handle context adaptation when evaluating fuzzy concepts. Procedures to determine context in different situations are provided. Context determination may be viewed as a kind of learning. An app...

Data mining tools generally deal with highly structured and precise data. However, classical methods fail to handle imprecise or uncertain information. This paper proposes a neuro-fuzzy data mining approach which provides a means to deal with the uncertainty of data. This presents a location-based service collaboration framework and uses the neuro-fuzzy algorithm for data mining. It also introd...

Recognition methods use different features to assign a pattern to a prototype class. The recognition accuracy strongly depends on the selected features. In this paper we present a novel fuzzy methodology to extract appropriate fuzzy features from the handwriting data. From these meaningful features a set of linguistic rules are derived which in turn constitute a fuzzy rule base for character re...

Fuzzy logic is achieved by formulating a rule base which is based on experience gathered by human operators. Those systems which cannot be modeled mathematically benefit most from Fuzzy control strategy since the imprecise data can be captured by using linguistic data in the rule-base. Fuzzy logic has certain disadvantages. The number of computations required for arriving at a certain output fo...

The objective of our study is to design an expert system by modelling the knowledge and thinking process of a doctor. A fuzzy logic controller (FLC) is used to model the process and a genetic algorithm (GA) helps to select a number of good rules from a manually constructed large rule base of an FLC, based on the opinion of 10 doctors. The GA-based tuning is done off-line. Once the optimized rul...