基于改进FOA-SVM的冲击地压危险性等级预测
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摘要: 对冲击地压危险性进行准确的预测预报对于防治冲击地压事故的发生至关重要。提出利用改进的果蝇优化算法(FOA)优化参数,建立模型实现对冲击地压危险性等级的预测。首先,利用文献提供的砚石台煤矿实测数据作为样本,选取影响冲击地压发生的十种主要因素如煤厚、埋深、倾角等,对数据进行归一化预处理和主成分分析。利用改进FOA的全局优化能力对SVM进行寻优,继而建立FOA-SVM模型;然后对23组训练样本进行训练,检验得模型误判率为0;最后将模型用于另外12组现场采集数据进行测试,并与标准FOA-SVM、PSO-SVM和GA-SVM预测结果进行比较。结果表明:改进的FOA-SVM模型适用于冲击地压危险性等级预测且预测精度较高。
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