Genetic Fuzzy Systems
Encyclopedia
Genetic fuzzy systems are fuzzy systems using a genetic algorithm
for determining the system parameters.
information, with mechanisms to deal with uncertainty and imprecision. With such remarkable attributes, fuzzy systems have been widely and successfully applied to control, classification and modeling problems (Klir and Yuan, 1995) (Pedrycz and Gomide, 1998).
One of the most important tasks in the development of fuzzy systems is the design of its knowledge base
. An expressive effort has been devised lately to develop or adapt methodologies that are capable of automatically extracting the knowledge base from numerical data. Particularly in the framework of soft computing, significant methodologies have been proposed with the objective of building fuzzy systems by means of genetic algorithms (GAs).
different components. As an example, the KB of a descriptive Mamdani-type fuzzy system has two components: a data base (DB), containing the definitions of the scaling factors and the membership functions of the fuzzy sets associated with the linguistic labels, and a rule base (RB), constituted by the collection of fuzzy rules.
Genetic algorithm
A genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems...
for determining the system parameters.
Fuzzy systems
Fuzzy systems are fundamental methodologies to represent and process linguisticLinguistics
Linguistics is the scientific study of human language. Linguistics can be broadly broken into three categories or subfields of study: language form, language meaning, and language in context....
information, with mechanisms to deal with uncertainty and imprecision. With such remarkable attributes, fuzzy systems have been widely and successfully applied to control, classification and modeling problems (Klir and Yuan, 1995) (Pedrycz and Gomide, 1998).
One of the most important tasks in the development of fuzzy systems is the design of its knowledge base
Knowledge base
A knowledge base is a special kind of database for knowledge management. A Knowledge Base provides a means for information to be collected, organised, shared, searched and utilised.-Types:...
. An expressive effort has been devised lately to develop or adapt methodologies that are capable of automatically extracting the knowledge base from numerical data. Particularly in the framework of soft computing, significant methodologies have been proposed with the objective of building fuzzy systems by means of genetic algorithms (GAs).
Genetic algorithms
Genetic algorithms have demonstrated to be a powerful tool to perform tasks such as generation of fuzzy rule base, optimization of fuzzy rule bases, generation of membership functions, and tuning of membership functions (Cordón et al., 2001a). All these tasks can be considered as optimization or search processes. Fuzzy system generated or adapted by genetic algorithms are called Genetic Fuzzy Systems (Cordón et al., 2001b). The combination of Fuzzy Systems with Genetic Algorithms have great acceptance in the scientific community, once these algorithms are robust and can search efficiently large solution spaces (Yuan and Zhuang, 1996).Genetic fuzzy systems
The first step in designing a Genetic Fuzzy System is to decide which parts of the knowledge base (KB) are subject to optimization by the GA. The KB of a fuzzy system does not constitute a homogeneous structure but is rather the union of qualitativelydifferent components. As an example, the KB of a descriptive Mamdani-type fuzzy system has two components: a data base (DB), containing the definitions of the scaling factors and the membership functions of the fuzzy sets associated with the linguistic labels, and a rule base (RB), constituted by the collection of fuzzy rules.