[1]吴晓军,杨 磊,张玉梅,等.基于遗传规划算法的Lorenz序列多步预测方法研究[J].西安建筑科技大学学报:自然科学版,2013,45(03):447-451,456.[doi:10.15986/j.1006-7930.2013.03.024]
　WU Xiao-jun,YANG Lei,ZHANG Yu-mei,et al.Multi-step prediction methods for Lorenz series based on GP algorithm[J].J.Xi’an Univ. of Arch. & Tech.:Natural Science Edition,2013,45(03):447-451,456.[doi:10.15986/j.1006-7930.2013.03.024]
点击复制

基于遗传规划算法的Lorenz序列多步预测方法研究()
分享到：

西安建筑科技大学学报:自然科学版[ISSN:1006-7930/CN:61-1295/TU]

卷:
45
期数:
2013年03期
页码:
447-451,456
栏目:
出版日期:
2013-06-30

文章信息/Info

Title:
Multi-step prediction methods for Lorenz series based on GP algorithm
文章编号:
1006-7930(2013)03-0447-05
作者:
吴晓军1; 2; 杨 磊1; 张玉梅1; 2; 马 悦2
(1.西北工业大学自动化学院,陕西 西安 710072;2.陕西师范大学计算机科学学院,陕西 西安710062)
Author(s):
WU Xiao-jun1; 2; YANG Lei1; ZHANG Yu-mei1; 2; MA Yue2
(1.College of Automation, Northwestern Polytechnical University, Xian 710072,China; 2.School of Computer Science, Shaanxi Normal University, Xian 710062,China)
关键词:
遗传规划算法; Lorenz系统; 多步预测
Keywords:
GP algorithm;  Lorenz system;  multi-step prediction
DOI:
10.15986/j.1006-7930.2013.03.024
文献标志码:
A
摘要:
Lorenz序列是由Lorenz系统产生的一组离散的时间序列,在Lorenz序列混沌特性的基础上提出了一种基于改进的GP算法的Lorenz序列预测方法.针对Lorenz序列预测模型求解,在GP算法中引入多种群及爬山算法,建立了Lorenz序列预测模型,在此基础上通过粒子群优化算法对预测模型参数进行优化,通过优化后的预测模型对Lorenz序列进行预测.最后通过实验对预测模型进行评价,结果表明,利用本文提出的方法获得的预测模型能有效的对Lorenz序列进行预测
Abstract:
Lorenz sequence is a set of discrete time series generated by the Lorenz system. Proposed is in this paper, a Lorenz system prediction method based on the improved GP algorithm on the basis of Lorenz’s chaotic characteristics. For solving Lorenz series prediction problems, multi-population and hill-climbing algorithms were introduced into GP algorithm and then the Lorenz series model was built by using this method. The particle swarm optimization is used to optimize the parameters of the model and then optimized model is used to predict the Lorenz series. Results of the model evaluation experiments showed that the prediction model obtained by the proposed method in this paper can effectively be used to predict the Lorenz series

参考文献/References:

[1] 吕金虎, 张锁春. 加权一阶局域法在电力系统短期负荷预测中的应用 [J]. 控制理论与应用 ,2002,19(5):767-770.
LJin-Hu,ZHANG Suo-Chun.Applicationofadding_weightone_ranklocal-region methodinelectric powersystemshort-termloadforecast[J].Journal ofcontroltheoryandapplications,2002,19(5):767-770.
[2] 崔万照, 朱长纯, 保文星, 等. 混沌时间序列的支持向量机预测[J]. 物理学报,2004,53(10):3303-3310.
CUI Wan-Zhao,ZHU Chang-chun,BAO Wen-xing, etal.Predictionofthechaotictimeseries usingsupportvectormachines[J].Actaphysicasinica,2004,53(10):3303-3310.
[3] 张家树, 肖先赐. 混沌时间序列的 Volterra 自适应预测[J]. 物理学报,2000,49(3):403-408.
ZHANGJia-shu,XIAO Xian-ci.Predictinglow-dimensionalchaotictimeseries usingvolterraadaptivefilers[J].Act-aphysicasinica,2000,49(3):403-408.
[4] WONG W K, XIA Min, CHU W C.Adaptiveneuralnetwork modelfortime-seriesforecasting [J].EuropeanJour-nal of Operational Research, 2010:807-816.
[5] ZHOU Quan,SUN Cai-xin,LEI Shao-lan,etal.RBF Neural Networkand ANFIS-Based Short-Term Load Forecas-ting Approachin Real-Time Price Environment[J].Power Systems,IEEE Transactions on,2008:853-858.
[6] KOZA J R.Genetic Programming II: Automatic Discovery of Reusable Programs [ M].Cambridge: The MITPress, 1994.
[7] LEE Yi-shian,TONG Lee-ing.Forecastingtimeseriesusinga methodologybasedonautoregressiveintegrated mov-ingaverageand genetic programming [J].Knowledge-Based System, 2011:66-72.
[8] WANGNER Neal, MICHALEWICZZbigniew, KNOUJA Moutaz, etal.TimeSeries Forecasting For Dynamic En-vironments: The DyFor Genetic Program Model [J].IEEE Transactions on Evolutionary Computation, 2007:433-452.
[9] ESTEVEZ P A, BECERRA-YOMA N, BORIC N,etal.Genetic Programming-based Voice Activity Detection[C].Electronics Letters29th, 2005,41(20):1141-1143.
[10] CAO Liang-yue.Practical methodfor determiningthe minimumembedding dimensionofascalartiemseries [J].Physica D, 1997(110):43-50.
[11] 吴晓军, 杨战中 , 赵 明 . 均匀搜索粒子群算法[J]. 电子学报,2011,39(6):1621-1266.
WU Xiao-jun,YANG Zhan-zhong,ZHAO Ming.A uniform searching particle swarm optimization algorithm[J].Chinesejournal ofelectronics,2011,39(6):1621-1266.
[12] XIE Xiao-feng, ZHANG Wen-jun, YANG Zhi-lian.A Dissipative Particle Swarm Optimization[C] ∥Congress onEvolutionary Computation (CEC), Hawaii, USA, 2002:1456-1461.

备注/Memo

备注/Memo:
收稿日期:2012-10-31 修改稿日期:2013-05-05
基金项目:国家自然科学基金资助项目(11172342);教育部“新世纪优秀人才支持计划”项目(NCET-11-0674);陕西省自然科学基础研究计划项目(2012JQ8051)
作者简介:吴晓军(1970-),男,陕西凤翔人,硕士,教授,主要从事非线性语音信号处理研究.
更新日期/Last Update: 2015-10-05