接受概率 meaning in Chinese

acceptance probability

The artificial neural net ( ann ) way is universal regard as one of the most effective ways of stlf . in this paper , some research is developed for stlf using ann ways in several parts : the first part is about the arithmetic of ann based on bp model , namely the advanced of traditional bp arithmetic , one alterable step and scale bp arithmetic based on comparability of model and probability of accepting bp arithmetic is used to enhances a lot the convergence rate of learning process of bp network , but also avoid the stagnation problem to some extent . it indicates that the ann ' s efficiency and precision by the way can be ameliorated by the simulation of real data
神经网络方法在短期预测中已经被公认为较有效的方法，本文针对神经网络用于电力系统短期负荷预测的几个方面展开研究工作：第一部分研究一般用于负荷预测的神经网络bp模型的算法，即对传统的bp算法的改进，将一种基于模式逼近度和接受概率的变步长快速bp算法应用到短期负荷预测，仿真结果表明该方法有效的改善了bp算法收敛速度慢以及容易陷入局部最小点的缺点，从而提高了神经网络用于负荷预测的效率和精度。