基于最小二乘支持向量机的煤矿瓦斯预测

Prediction of Gas Emission Based on Least Squares Support Vector Machines

瓦斯涌出量受多种自然因素和开发技术的影响,是一个非线性、高维的问题.提出了改进的PSO算法与LSSVM算法相结合对瓦斯涌出量进行预测的新方法.实验结果表明,该模型预测精度更高,泛化能力更强.

Gas emission is influenced by series natural factors and exploiting conditions,which is a non-linearly and high-dimension problem.A new method of combining the improved PSO with LSSVM is presented to predict gas emission.Experimental results show that the model can achieve more accurate prediction and stronger generative ability.