DocumentCode :
2770891
Title :
Fast Incremental Learning Algorithm using Evolutionary Logic Networks for Real-Value Inputs
Author :
Park, Myoung Soo ; Choi, Jin Young
Author_Institution :
Seoul Nat. Univ., Seoul
fYear :
0
fDate :
0-0 0
Firstpage :
2047
Lastpage :
2054
Abstract :
In this paper, we propose a new incremental learning algorithm which uses a new type of experience to reduce the computation time without the aid of addition information. The data structure, evolutionary logic networks for real-valued inputs (ELN-R) for storing and using this experience is defined and an incremental learning algorithm for ELN-R is described. The performance of the proposed learning algorithm is tested through experiments on two-spiral problem which is selected as a benchmark problem to compare the performance of the proposed algorithm with those of other algorithms.
Keywords :
data structures; evolutionary computation; learning (artificial intelligence); data structure; evolutionary logic; evolutionary logic networks; fast incremental learning algorithm; Backpropagation algorithms; Benchmark testing; Computer networks; Computer science; Costs; Data mining; Data structures; Logic; Neural networks; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246973
Filename :
1716363
Link To Document :
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