全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于BMACRLS模型的复杂系统行为预测方法及其应用*

, PP. 266-270

Keywords: 行为预测,神经网络,主成分分析(PCA),递推最小二乘,电力负荷预测

Full-Text   Cite this paper   Add to My Lib

Abstract:

复杂系统行为预测是复杂系统管理与决策的重要内容.为了在确保预测准确性的前提下提高系统预测的稳定性和泛化能力,提出一种基于主成分分析结合加入B样条的连续CMAC递推最小二乘算法(CMACRLS)的组合模型的预测方法(PCABMACRLS).首先利用主成分分析来降低输入变量的维数以减少CMAC权系数空间.其次采用BMACRLS算法以确保权值的收敛且能提供函数的微分信息以适合复杂系统的在线建模.最后以实际应用为例,对比采用RBF神经网络模型和本文的PCABMACRLS组合模型的预测实验.实验结果显示,本文方法具有稳定性好、泛化能力强、运行速度快、预测精度高等显著优点.

References

[1]  Yang H T, Huang C M. Identification of ARMAX Model for Short Term Load Forecasting: An Evolutionary Programming Approach. IEEE Trans on Power System, 1996, 11(1): 403408
[2]  Papalexopoulos A D, Hesterberg T C. A Regression Based Approach to Short Term System Load Forecasting. IEEE Trans on Power Systems, 1990, 5(4): 15351547
[3]  Pan Feng, Cheng Haozhong, Yang Jingfei, et al. Power System ShortTerm Load Forecasting Based on Support Vector Machines. Power System Technology, 2004, 28(21): 3942 (in Chinese) (潘 峰,程浩忠,杨镜非,等.基于支持向量机的电力系统短期负荷预测.电网技术, 2004, 28(21): 3942)
[4]  Rahman S. Generalized KnowledgeBased Short Term Load Forecasting Techniques. IEEE Trans on Power Systems, 1993, 8(2): 508514
[5]  Albus J S. A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller. Journal of Dynamic Systems, Measurement and Control, 1975, 97(3): 220227
[6]  Parks P C, Militzer J. Convergence Properties of Associative Memory Storage for Learning Control System. Automation and Remote Cotnrol, 1989, 50(10): 254286
[7]  Commuri S, Jagannathan S, Lewis F L. CMAC Neural Network Control of Robot Manipulators. Journal of Robotic Systems, 1997, 14(6): 465482
[8]  He Jianchun, Wang Huiyan. Application of CMAC Neural Network to Nonlinear Predictive Control. Control and Decision, 2002, 17(1): 9295 (in Chinese) (何剑春,王慧艳.CMAC网络建模在非线性预测控制中的应用.控制与决策, 2002, 17(1): 9295)
[9]  Ruan Qing, Wang Yiqiang. PCA Approach to BP Learning. Journal of Fudan University: Natural Science, 2005, 44(2): 318322,327 (in Chinese) (阮 庆,王逸蔷.主成份分析法在BP学习中的应用.复旦学报:自然科学版, 2005, 44(2): 318322,327)
[10]  Qin Ting, Chen Zonghai, Zhang Haitao, et al. A Learning Algorithm of CMAC Based on RLS. Neural Processing Letters, 2004, 19(1): 4961
[11]  Thompson D E, Kwon S. Neighbor Sequential and Random Training Techniques for CMAC. IEEE Trans on Neural Networks, 1995, 6(1): 196202
[12]  Wang Shengfu. Spline Function and Their Application. Fremont, USA: Northwestern Polytechnical University Press,1989
[13]  Chen S, Cowan C F N,Grant P M. Orthogonal Least Squares Learning Algorithm for Radial Basis Function Networks. IEEE Trans on Neural Networks, 1991, 2(2): 302309
[14]  Chen Jianhua, Zhou Hao. ShortTerm Electricity Price Forecasting Using Cerebellar Model Articulation Controller Neural Network. Power System Technology, 2003, 27(8): 1620 (in Chinese) (陈建华,周 浩.基于小脑模型关节器神经网络的短期电价预测,电网技术,2003,27(8):1620)

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133