基于改进的切比雪夫神经网络的露天煤矿产量预测

Surface coal mine production forecast based on improved Chebyshev neural network

由于影响露天煤矿产量的因素众多,尚未有精确方法对其进行预测。本文针对切比雪夫神经网络存在的不足,从算法和网络结构方而进行了综合改进。改进后的切比雪夫神经网络,符合生物神经网络的基本特征,算法简单,收敛速度快。用改进的切比雪夫神经网络对露天煤矿原煤产量进行建模和预测,结果表明,此种改进方法不仅提供了一种有效的预测露天矿原煤产量方法,具有优良的预测能力,而且在相同精度的前提下,其收敛速度也优于一般的BP网络,为露天煤矿的生产提供科学、合理的决策依据。

Many factors affect the production of surface coal mine,but there is no accurate way to predict it.In this paper,aim at Chebyshev neural network weaknesses,carry out a comprehensive improvement from the algorithm and network structure.Improved Chebyshev neural network in line with the basic characteristics of biological neural networks,the algorithm simple and fast convergence.Using the modified Chebyshev neural networks to predict open pit coal production,the results show that this method not only provides an effective open-pit coal production forecast method with good predictive ability,but also in the same precision under the premise of the convergence speed is superior to the general BP network,can provide scientific and rationalr decision making for open pit production.