【摘要】 针对ＢＰ网络的缺陷，提出了基于拟牛顿法的自适应算法和改进的遗传算法，以提高神经网的学习效率，克服ＢＰ网络的局部收敛性的缺点，形成一种新的神经网与遗传算法相结合的短期负荷预测模型。实测结果表明该模型和算法具有良好的性能和较高的预测精度更多还原

【Abstract】 This paper presents a new hybrid artificial neural network (ANN) learning algorithm, which combines the adapted learning algorithm based on quasi Newton method and the improved genetic algorithms (GA) It possesses merits of high speed of convergence and higher precision A new hybrid short term load forecasting model is built with the above algorithms Satisfactory results are obtained by applying it to a certain network更多还原