基于熵值法的PSOBP神经网络私家车保有量的预测

英文篇名：Total Number of Private Cars Prediction Based on Entropy-based PSOBP Neural Network
中文刊名：电脑知识与技术
英文刊名：Computer Knowledge and Technology
作者：杨华 ; 周锐
英文作者：YANG Hua ; ZHOU Rui(School of Computer Science and Technology ; China University of Mining and Technology ; Xuzhou 221116 ; China)
中文关键词：粒子群 ; 神经网络 ; 私家车保有量 ; 权值和阈值
英文关键词：particle swarm ; neural network ; private car ownership ; weights and threshold value ; entropy ; simulated annealing
出版日期：2011-07-05
机构：中国矿业大学计算机科学与技术学院;
年：2011
期：19
出版单位：电脑知识与技术

摘要

为解决现有的BP神经网络对私家车保有量的预测中存在的对初始权值和阈值敏感、易陷入局部极小点和收敛速度慢等问题,针对粒子群算法具有全局搜索寻优的特点,该文提出了基于熵值法的采用粒子群算法优化的BP神经网络的模型。我们用新建立的模型进行私家车保有量的预测,并将其结果与传统BP算法以及模拟退火法进行比较,结果表明新的模型有效的防止了网络陷入局部极小值的可能,明显提高了神经网络模型预测的速度和准确性。
In order to solve the existing problems such as the initial weights and threshold-sensitive,easily falling into local minima and slow convergence in the total number prediction of private cars by using BP neural network,this paper proposes the use of entropy-based particle swarm optimization algorithm BP neural network model.And we will use the model to predict the amount of private cars study and compare its results with the traditional BP algorithm and simulated annealing method.The results show that the new model is effective to prevent the network may fall into local minima and significantly improve the speed and accuracy of neural network model.

引文

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