Self-Organizing Operator Maps in Complex System Analysis

Autor:	Pasi Lehtimäki, Kimmo Raivio, Olli Simula
Rok vydání:	2003
Předmět:	Self-organizing map Soft computing Decision support system Fuzzy rule Artificial neural network business.industry Computer science Machine learning computer.software_genre Fuzzy logic ComputingMethodologies_PATTERNRECOGNITION Operator (computer programming) Artificial intelligence business computer
Zdroj:	Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 ISBN: 9783540404088 ICANN
DOI:	10.1007/3-540-44989-2_74
Popis:	The growth in amount of data available today has encouraged the development of effective data analysis methods to support human decision-making. Neuro-fuzzy computation is a soft computing hybridisation combining the learning capabilities of the neural networks with the linguistic representation of data provided by the fuzzy models. In this paper, a framework to build temporally local neuro-fuzzy systems for the analysis of nonstationary process data using self-organizing operator maps is described.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d6e4a0d89e3c87a2a966aa9e16469719 https://doi.org/10.1007/3-540-44989-2_74 Zobrazit plný text záznamu