基于神经网络的煤矿企业经营绩效评价研究

针对煤矿企业经营绩效受自然地质条件影响较大，对产生相应的“级差”特点，先采用ANN模型对煤矿企业的基础条件存在“级差”进行的识别，有效地剔除了这些“级差”对煤矿企业经营绩效的“贡献”，实现了评价的“公平性”；然后，建立了基于ANN煤矿企业经营绩效综合评价与排序模型，避免了专家评分法等主观赋权法定权的客观性不足，更为科学地反映煤矿绩效的优劣。再次，建立基于ANN的煤矿企业经营绩效与其影响因素之间相互关系的分析模型，为企业发现薄弱环节，改进管理提供有力工具。最后，将这些模型应用于高产高效矿井经营绩效的实际评价进行了实证研究，取得了良好的效果。

Research on evaluation of operational performance of coal mines based on ANN

Aimed at the natural and geological condition in coal mines being greater influence on their performance,and resulting in the differential in their input and output,a classification model based on ANN has been used to identify the differential in their basic condition, and eliminated the contribution of their influence to performance of the coal mine effect to realize fair evaluation. The synthesis evaluation and arrangement model on operational performance of the coal mine based on ANN has been put forward,avoiding the shortage objectiveness of subjective determine the weight, such as expert evaluation etc, and reflecting the operational performance of coal mine scientifically. And then a model analysis relation between the operational performance of coal mine and its influence factors based on ANN has been built,it provides an useful tool for enterprises to find out their weakness and improve their management. Finally,those models have been used to practical evaluate the operation performance of high output and high efficiency coal mine, and given the good effect.