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计算机系统应用英文版:2014,23(4):135-137,143

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基于改进粒子群优化算法的BP预测模型

王行甫, 陈宏亮

(中国科技大学计算机科学与技术学院, 合肥 230027)

BP Forecast Model Based on Improved PSO Algorithm

WANG Xing-Fu, CHEN Hong-Liang

(Compute Science and Technology, University of Science and Technology of China, Hefei 230027, China)

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本文已被：浏览 1354次下载 3074次
Received:August 30, 2013 Revised:October 14, 2013

中文摘要: 该论文提出了基于改进粒子群优化的BP算法. 在该算法中，通过对粒子群优化算法中的惯性权重的计算方法的改进，同时利用改进的PSO算法替代了BP算法中的梯度下降算法，使得改进后的算法具有不易与陷入局部极小等优点. 并将该算法利用在预测气温上，实验证明：改进后的算法在预测模型上能够取得较好的预测效果，提高预测精度.

中文关键词: 粒子群算法 BP算法气温预测惯性权值梯度下降算法

Abstract:A BP prediction model which based on improved PSO algorithm is proposed in this essay, in this algorithm, I modify the way to calculate the inertia weight, and use the improved PSO algorithm instead of the gradient descent algorithm, Make this changes it will not fall into local minimum. And use this way to forecast the weather, through the experiment result I find that the improved algorithm has high efficiency, and it also improve the prediction accuracy.

keywords: PSO BP algorithm weather forecast inertia weight gradient descent algorithm

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基金项目:国家科技重大专项（2012ZX10004301-609）

Author Name	Affiliation
WANG Xing-Fu	Compute Science and Technology, University of Science and Technology of China, Hefei 230027, China
CHEN Hong-Liang	Compute Science and Technology, University of Science and Technology of China, Hefei 230027, China

Author Name	Affiliation
WANG Xing-Fu	Compute Science and Technology, University of Science and Technology of China, Hefei 230027, China
CHEN Hong-Liang	Compute Science and Technology, University of Science and Technology of China, Hefei 230027, China

引用文本：
王行甫,陈宏亮.基于改进粒子群优化算法的BP预测模型.计算机系统应用,2014,23(4):135-137,143
WANG Xing-Fu,CHEN Hong-Liang.BP Forecast Model Based on Improved PSO Algorithm.COMPUTER SYSTEMS APPLICATIONS,2014,23(4):135-137,143