基于人工免疫算法的神经网络电力系统短期负荷预测

在BP神经网络（Baek-propagatlon 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AJA-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．

Power System Short-term Load Forecasting Based on Artificial Immune Algorithm Neural Network

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.