Being aimed at the main defects of slowly learning convergent velocity of the BP neural network, lots of improved plans such as improving excitation function, improving error function, improving general error, the self-adaptation adjustment of learning factor and inertial factor, the combination of the gradient method and the direct searching method, general optimization, non-linear optimization, and topology correcting algorithm are classified and summarized beased on the principles of the improvements.
针对BP网络的学习收敛速度慢这一主要缺陷,对改进激励函数、改进误差函数、改进一般化误差、学习因子和惯性因子的自适应调整、梯度下降法与直接搜索法相结合、全局优化、非线性优化、拓仆修正算法等多种改进方案按改进原理进行了分类综述,并在此基础上,通过解决XOR问题的仿真实验对部分改进方案进行实验性评价,分析说明了它们的优劣和特点。