Paper Title:
Near Optimal Learning Rate BP Algorithm and its Application in Traffic Forecast
  Abstract

Aimed at the inadequacy of the standard BP algorithm, a near optimal learning rate BP algorithm (NOLRBP) is presented. Selecting the learning rate of the algorithm based on one-dimensional search algorithm of optimization theory avoids the blindness in determining the learning rate. Simulations show that the algorithm is superior to the standard BP algorithm (SDBP), momentum BP algorithm (MOBP) and variable learning rate BP algorithm (VLBP).

  Info
Periodical
Chapter
Chapter 8: System Modeling and Simulation
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
4513-4517
DOI
10.4028/www.scientific.net/AMM.121-126.4513
Citation
L. M. Qin, H. T. Zhang, "Near Optimal Learning Rate BP Algorithm and its Application in Traffic Forecast", Applied Mechanics and Materials, Vols. 121-126, pp. 4513-4517, 2012
Online since
October 2011
Export
Price
$32.00
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