An Adaptable Gaussian Neuro-Fuzzy Classifier
| Autor: | Dimitrios S. Frossyniotis, Minas Pertselakis, Andreas Stafylopatis |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Fuzzy rule
Artificial neural network Computer science business.industry Gaussian Intelligent decision support system Novelty Initialization Machine learning computer.software_genre Fuzzy logic symbols.namesake symbols Context awareness Artificial intelligence business Classifier (UML) Gaussian process computer |
| Zdroj: | Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 ISBN: 9783540404088 ICANN |
| DOI: | 10.1007/3-540-44989-2_110 |
| Popis: | The concept of semantic and context aware intelligent systems provides a vision for the Information Society where the emphasis lays on computing applications that can sense context from the people and the environment and wrap that knowledge into adaptable behavior. In this framework the proper and automatic classification of data gathered by sensors is of major importance. Our approach describes a model that operates as a self-evaluating classifier using on-line re-clustering, addressing adequately the basic issues of modern demands. The novelty of the model lies in a flexible and efficient initialization technique that first partitions the data space utilizing Gaussian distributions and then merges clusters so as to produce an effective partitioning. |
| Databáze: | OpenAIRE |
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