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现代矿业 ›› 2011, Vol. 27 ›› Issue (3): 37-39.

• 安全与环保 • 上一篇    下一篇

采煤工作面瓦斯抽采率预测的神经网络模型

张明,冯涛,朱卓慧   

  1. 湖南科技大学
  • 出版日期:2011-03-08 发布日期:2011-03-10
  • 基金资助:

    *国家重点自然科学基金项目(编号:50834005)

Neural Network Model of Gas Extraction Rate Prediction at Coal Face

Zhang Ming,Feng Tao,Zhu Zhuohui   

  1. Hunan University of Science and Technology
  • Online:2011-03-08 Published:2011-03-10

摘要: 由于采煤工作面瓦斯抽采率影响因素复杂多样,且各影响因素之间存在着动态、模糊的非线性关系,传统的预测方法难以建立其预测模型。神经网络具有自组织、自适应、并行处理等特性和很强的非线性逼近能力,通过采煤工作面瓦斯抽采率和其影响因素之间的函数关系建立了预测模型。结果表明,预测模型精度能够满足要求,具有合理性和可行性。

关键词: 瓦斯抽采率, 神经网络, 预测

Abstract: As influencing factors of gas extraction rate at coal face are complicated, nonlinear relation which are dynamic and vague exist between each influencing factors, prediction model is hard to establish on traditional prediction methods. Neural network has the characteristics of self-organization, self-adaptive, parallel processing and strong nonlinear approximation ability. The prediction model was established based on functional relationship between gas extraction rate at coal face and its influencing factors. The result indicates that the precision of the prediction model could meet the request, and the model is reasonable and feasible.

Key words: Gas extraction rate, Neural network, Prediction