Evolving computational intelligence systems
Published 1 March 2005
Plamen Angelov, Nikola Kasabov
Citations55
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TL;DR
A new generation of computational intelligent systems is introduced in a generic framework of the evolving computational intelligence systems (ECIS) that develop, unfold their structure and functionality from incoming data that forms the conceptual basis for the development of the truly intelligent systems.
Abstract
Abstract—A new paradigm of the evolving computational intelligence systems (ECIS) is introduced in a generic framework of the knowledge and data integration (KDI). This generalization of the recent advances in the development of evolving fuzzy and neuro-fuzzy models and the more analytical angle of consideration through the prism of knowledge evolution as opposed to the usually used datacentred approach marks the novelty of the present paper. ECIS constitutes a suitable paradigm for adaptive modeling of continuous dynamic processes and tracing the evolution of knowledge. The elements of evolution, such as inheritance and structure development are related to the knowledge and data pattern dynamics and are considered in the context of an individual system/model. Another novelty of this paper consists of the comparison at a conceptual level between the
Keywords
Computer Science
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