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基于IPSO-SVR模型的煤层底板突水量预测 被引量:2
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作者 王鹏 朱希安 +1 位作者 王占刚 刘德民 《北京信息科技大学学报(自然科学版)》 2021年第1期40-44,共5页
为准确预测煤层底板突水量,提出了一种基于IPSO-SVR(改进的粒子群算法以优化支持向量回归机算法)的煤层底板突水量的预测模型。针对矿井底板突水这种非线性、小样本问题,通过改变粒子群算法的惯性权重因子定义以及引入混沌映射思想的方... 为准确预测煤层底板突水量,提出了一种基于IPSO-SVR(改进的粒子群算法以优化支持向量回归机算法)的煤层底板突水量的预测模型。针对矿井底板突水这种非线性、小样本问题,通过改变粒子群算法的惯性权重因子定义以及引入混沌映射思想的方式,避免算法陷入局部最优值,强化全局搜索。结合王家岭等煤矿突水实例,将水压、含水层、隔水层厚度、底板破坏深度以及断层落差作为影响煤层底板突水量的特征因素,将该预测模型算法与PSO-SVR预测模型算法进行比较。仿真结果表明:该预测模型算法的预测值更接近实际值,具有一定实际应用价值。 展开更多
关键词 矿井 IPSO-SVR模型 煤层底板突水量 参数优化
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Water inrush evaluation of coal seam floor by integrating the water inrush coefficient and the information of water abundance 被引量:3
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作者 Shi Longqing Qiu Mei +2 位作者 Wei Wenxue Xu Dongjing Han Jin 《International Journal of Mining Science and Technology》 SCIE EI 2014年第5期677-681,共5页
The method of singular coefficient of water inrush to achieve safety mining has limitation and one sidedness. Aiming at the problem above, large amounts of data about water inrush were collected. Then the data, includ... The method of singular coefficient of water inrush to achieve safety mining has limitation and one sidedness. Aiming at the problem above, large amounts of data about water inrush were collected. Then the data, including the maximum water inrush, water inrush coefficient and water abundance in aquifers of working face, were processed by the statistical analysis. The analysis results indicate that both water inrush coefficient and water abundance in aquifers should be taken into consideration when evaluating the danger of water inrush from coal seam floor. The prediction model of safe-mining evaluation grade was built by using the support vector machine, and the result shows that this model has high classification accuracy. A feasible classification system of water-inrush safety evaluation can be got by using the data visualization method which makes the implicit support vector machine models explicit. 展开更多
关键词 Floor water inrush Water inrush coefficient Water abundance Units-inflow Support vector machine
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