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Title Details:
Classic Computational Intelligence Extensions
Authors: Kampourlazos, Vasileios
Papakostas, Georgios
Reviewer: Kechagias, Athanasios
Subject: MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS
Description:
Abstract:
The aforementioned methodologies of classical Computational Intelligence are extended through synergies among them and/or adopting alternative computational techniques such as machine learning techniques, etc. Specifically, combinations of neural networks and fuzzy system models are proposed, which can be optimized using evolutionary computation. In this context, decision trees based on rules are presented as an extension of fuzzy system rules. Following a similar approach, radial basis function networks are introduced as an alternative to fuzzy systems. Additionally, K-nearest neighbor networks are presented as an alternative to neural networks.
Linguistic Editors: Violitzi, Georgia
Type: Chapter
Creation Date: 2015
Item Details:
License: http://creativecommons.org/licenses/by-nc-nd/3.0/gr
Handle http://hdl.handle.net/11419/3447
Bibliographic Reference: Kampourlazos, V., & Papakostas, G. (2015). Classic Computational Intelligence Extensions [Chapter]. In Kampourlazos, V., & Papakostas, G. 2015. Introduction to Computational Intelligence [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/3447
Language: Greek
Is Part of: Introduction to Computational Intelligence
Publication Origin: Kallipos, Open Academic Editions