DocumentCode
383284
Title
Evolving connectionist systems for adaptive learning and knowledge discovery: Methods, tools, applications
Author
Kasabov, Nikola
Author_Institution
Knowledge Eng. & Discovery Res. Inst., Atickland Univ. of Technol., Auckland, New Zealand
Volume
1
fYear
2002
fDate
2002
Firstpage
24
Abstract
The paper describes what evolving processes are and presents a computational model called evolving connectionist systems (ECOS). The model is based on principles from both brain organization and genetics. The applicability of the model for dynamic modeling and knowledge discovery in the areas of brain study, bioinformatics, speech and language learning, adaptive control and adaptive decision support is discussed.
Keywords
adaptive control; data mining; learning (artificial intelligence); neural nets; adaptive control; adaptive decision support; adaptive learning; bioinformatics; brain organization; computational model; connectionist systems; dynamic modeling; evolving connectionist system; genetics; knowledge discovery; language learning; speech; Adaptive control; Adaptive systems; Biological neural networks; Brain modeling; DNA; Information processing; Natural languages; Neurons; RNA; Speech;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium
Print_ISBN
0-7803-7134-8
Type
conf
DOI
10.1109/IS.2002.1044223
Filename
1044223
Link To Document