Title :
A Study on How to Help Back-propagation Escape Local Minimum
Author :
Chai, Shaobin ; Zhou, Yong
Author_Institution :
Dalian Univ. of Technol., Dalian
Abstract :
One peculiarity impairing the performance of back-propagation is the presence of local minimum. In this paper, a local minimum detection algorithm called LMD is advocated. LMD bases on two kinds of constraint of local minimum to detect and escape local minimum. Before back-propagation trapping into local minimum, LMD will take measure to rectify the adjusting method of weights and biases. Combining LMD, back-propagation is improved to LMDBP algorithm in this paper. Results of experiment of back-propagation and LMDBP indicate that LMDBP can escape local minimum much more sufficiently than back-propagation algorithm.
Keywords :
backpropagation; adjusting method; backpropagation escape local minimum algorithm; backpropagation trapping; Backpropagation; Detection algorithms; Feedforward neural networks; Feedforward systems; Genetic algorithms; Mathematics; Neural networks; Software algorithms; Software performance;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.150
