Power Load Forecast Model of Genetic Neural Network Based on Tabu Search

摘要：

The neural network has been applied to the area of power load forecast successfully, but it has such disadvantages of local optimization and slow convergence speed. A new kind of genetic neural network forecast model based on tabu search was proposed for overcoming those disadvantages. Utilizing the global optimizing ability of genetic algorithm and the memory function and ability of mountain climbing of tabu search, it defined a tabu aberrance operator and constructed a mixed genetic tabu algorithm, which can solve the above disadvantages of neural network and the premature problems of genetic algorithm, to train the weights and thresholds of neural network. Comparing with normal genetic algorithms, this genetic neural network based on tabu search achieved better forecast result.

作者: Wang SHU-LING Gu ZHI-HONG Li ZHEN-TAO

作者单位: North China Electric Power University, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）