DocumentCode :
2772672
Title :
A Proposal to Solve N-Queens Problems Using Maximum Neuron Model with A Modified Hill-Climbing Term
Author :
Noguchi, Wataru ; Pham, Cong-Kha
Author_Institution :
NEC, Tokyo
fYear :
0
fDate :
0-0 0
Firstpage :
2679
Lastpage :
2682
Abstract :
An effective solving method with a modified hill-climbing term which is applied to a maximum neuron model for the N-Queens problems is proposed. In which, a first model using a gradient ascent learning for determining A and B coefficients, a second model using fixed A and B coefficients which are determined by an upper bound of an input value to a neuron, and a third model using modified initial values which applied to the second model, have been adopted. As a result, calculation times are reduced when compared with the previous methods.
Keywords :
Hopfield neural nets; learning (artificial intelligence); problem solving; N-Queens problem solving; gradient ascent learning; maximum neuron model; modified hill-climbing term; Equations; Hopfield neural networks; National electric code; Neural networks; Neurons; Optimization methods; Proposals; Upper bound;
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.2006.247149
Filename :
1716459
Link To Document :
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