计算机技术与发展Issue(10)：36-40,5.DOI:10.3969/j.issn.1673-629X.2013.10.009
一种新参数优化算法及其在流量预测中的应用
A New Parameter Optimization Algorithm and Its Application in Traffic Prediction
摘要
Abstract
For improving the prediction accuracy of network traffic,a new network traffic prediction model is proposed based on wavelet transform and optimized LS-SVM. To optimize the parameters of LS-SVM,a kind of adaptive chaos quantum-behaved particle swarm optimization based on simulated annealing algorithm ( AS-QPSO) is proposed. The algorithm joins adaptive and chaotic characteristics based on QPSO,making it dynamic adaption,improving the capacity of the global optimization. Then the simulated annealing algorithm is introduced to avoid falling into local optimum,the algorithm has better convergence and stability. Experimental results show that com-pared with other algorithm optimized LS-SVM model,the proposed model is more efficient with higher precision,better generalization performance and stability.关键词
量子粒子群算法/参数优化/小波变换/最小二乘支持向量机/流量预测Key words
quantum-behaved particle swarm optimization/parameters optimization/wavelet transformation/least squares support vector machines/traffic prediction分类
信息技术与安全科学引用本文复制引用
邓宗强,曾碧卿..一种新参数优化算法及其在流量预测中的应用[J].计算机技术与发展,2013,(10):36-40,5.基金项目
教育部科学研究青年基金项目(10YJC870044) （10YJC870044）
广东省自然科学基金资助项目(8151063101000040) （8151063101000040）
