基于自适应鲁棒性证据理论的煤层底板突水预测

基金项目:

中国博士后科学基金第53批面上资助项目（2013M530896）

山西省科技重大专项项目（20121101004）

山西省科技攻关项目(20130321004-01)

详细信息

Water inrush prediction of coal floor based on adaptive robust evidence theory

School of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, China

摘要: 针对D-S证据理论应用于煤层底板突水预测时，因其鲁棒性差、证据源冲突概率过大时融合结果不佳等问题而导致预测准确性不高的问题，在其改进形式——鲁棒性证据理论基础上，提出了一种自适应鲁棒性证据理论，并将自适应鲁棒性证据理论与多神经网络相结合，建立了一种煤层底板突水预测模型，采用某煤矿工作面实测水文地质数据对该模型进行了实验研究。实验结果表明，该模型预测结果准确率较高，稳定性好。
- 煤层底板 /
- 突水预测 /
- D-S证据理论 /
- 鲁棒性证据理论 /
- 自适应鲁棒性证据理论
Abstract: For low prediction accuracy of D-S evidence theory used in water inrush prediction of coal floor because of poor robust and fusion effect under the condition of large conflict probability of evidence source, an adaptive robust evidence theory was proposed based on robust evidence theory. A water inrush prediction model of coal floor was established by combining the adaptive robust evidence theory and multiple neural networks. The model was experimentally researched by use of real hydrogeololgy data of a coal mine working face. The experimental result shows that the model has high prediction accuracy and good stability.
- coal floor /
- water inrush prediction /
- D-S evidence theory /
- robust evidence theory /
- adaptive robust evidence theory