摘要
在BP神经网络(Back-propagation neural network,BPNN)模型中引入人工免疫算法(Artificial Immune Algo-rithm,AIA),给出了AIA-BPNN模型,基本思想是结合AIA算法的搜索特性和BPNN模型的优良性能,可以进一步提高学习能力.与实际电力系统结合构造了AIA-BPNN电力系统短期负荷预测模型,通过使用AIA算法,优化BPNN的权值和阈值,使BPNN权值和阈值选择的盲目性得以克服.
To put forward an AIA-BPNN model, artificial immune algorithrn（AIA） was introduced in BP neural networks（BPNN） model.In order to improve the capability of learning,the basic idea was to com- bine the searching feature of AIA with the excellent property of BPNN. Integrated with the actual power sys- tem, an AIA-BPNN power system short-term load forecasting model was constructed. The blindness of choosing the weights and thresholds of BPNN was conquered by using AIA to optimize the weights and thresholds of BPNN.
出处
《成都大学学报（自然科学版）》
2013年第2期159-161,共3页
Journal of Chengdu University（Natural Science Edition）
关键词
人工免疫算法
神经网络
电力系统
预测
artificial immune algorithm
neural network
power system
forecast
