The fuzzy support vector machine model was proposed based on membership of fuzzy set theory and support vector machine (SVM), which was used to assess the water inrush risk from coal floor.The optimal model parameters was determined by the training sample data in ten regions of Feicbeng mine area, and evaluated the water inrush risk of four test samples.Experimental results show that the model can reduce the complexity of the sample data processing,solve the small sample, nonlinear problem, and provided a new evaluation method for risk evaluation of water inrush from coal floor.%提出将模糊理论中的隶属度与支持向量机相结合的模糊-支持向量机模型,用于对煤层底板突水危险性的评价.在对肥城煤层底板突水危险性评价指标体系分析的基础上,通过对肥城矿区10个地段的样本数据训练确定最优的模型参数,并对4个测试样本进行了突水危险性评价.实验表明:该模型能够减少样本数据处理的复杂性,较好地解决小样本、非线性问题,为煤层底板突水危险性的评价提供了一种新方法.
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