首页|基于二次补偿策略的VMD-LSTM瓦斯浓度预测方法

基于二次补偿策略的VMD-LSTM瓦斯浓度预测方法

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瓦斯浓度过大可能会造成窒息、爆炸等安全事故,严重威胁着煤矿企业的安全生产.为了更好地监测瓦斯浓度,及时预防瓦斯事故,提出了基于二次分解策略的VMD-LSTM瓦斯浓度预测方法.该方法首先根据PSO算法确定惩罚因子与模态数的最佳参数组合,然后利用VMD分解瓦斯浓度数据进行LSTM的初次浓度预测,最后基于二次补偿策略,对初次结果补偿预测得到更高精度结果.试验表明,该方法有效提高了瓦斯预测精度,具有较好的现实推广应用价值.
VMD-LSTM Gas Concentration Prediction Method Based on Secondary Compensation Strategy
Excessive gas concentration may lead to safety accidents such as suffocation and explosion,posing a serious threat to the safe production of coal mining enterprises.In order to better monitor gas con-centration and prevent gas accidents in time,a VMD-LSTM gas concentration prediction method based on secondary decomposition strategy is proposed.This method firstly determines the optimal combination of pen-alty factor and modal number using the PSO algorithm.Then,VMD is utilized to decompose the gas concen-tration data for the initial concentration prediction of LSTM.Finally,based on a secondary compensation strategy,the initial results are compensated to obtain higher prediction accuracy.Experiments show that this method effectively improves prediction accuracy of gas,and has good practical application value.

LSTMconcentration predictiongasvariational mode decompositionk

孔金浩

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山东新矿赵官能源有限公司

长短时记忆网络 浓度预测 瓦斯 变分模态分解

2024

现代矿业
中钢集团马鞍山矿山研究院有限公司

现代矿业

影响因子:0.33
ISSN:1674-6082
年,卷(期):2024.40(7)