基于改进蚁群神经网络的短期负荷预测

在传统神经网络负荷预测的基础上，采用蚁群算法优化神经网络的权值，同时再用模糊逻辑对影响负荷的随机因素进行修正，提出了改进的蚁群神经网络算法。对四川某500kV变电站进行短期负荷预测，结果表明这一算法能获得较高的预测精度，是一种行之有效的短期负荷预测方法。

Short-term Load Forecasting Based on Improved Ant Colony Neural Network

Based on the traditional NN （neural network） load prediction, ant colony algorithm is used to optimize the weights of NN. Then, the fuzzy logic is used to modify the random factor which influences the load, and an ant colony neural network （ACONN） algorithm is proposed. Practical example indicates that the application is feasible and effective, which can obtain more accurate result than the conventional methods.