基于BP神经网络的煤矿沉陷补偿模型

Model of compensation for coal mine subsidence based on BP neural network

煤矿开采沉陷补偿以往传统的做法是专家评估的方法。把现代数学方法与煤矿沉陷补偿评估相结合提出新的模式,将BP神经网络理论应用于煤矿开采沉陷补偿评估预测中,在与目前常用的评估方法进行比较后,指出了用神经网络进行煤矿沉陷补偿预测的可行性和优势,讨论了网络的结构设计、学习算法,以及运用实例来进行验证。

The traditional compensation area for subsidence in coal mine is expert evaluation. The article expounds a new model, by applying the theory of neural networks to the subsidence area compensation evaluation. After comparing with the normal method, the article points out the validity and advantages of the subsidence area compensation model, and the problems in the article also discusses designing and training of neural netwok, at last, uses the an instance to verify the theory.