辽宁工程技术大学学报（自然科学版）2023，Vol.42Issue(6)：733-739,7.DOI:10.11956/j.issn.1008-0562.2023.06.013
自适应增强优化的瓦斯涌出量预测模型
Prediction model of gas emission based on adaptive enhancement optimization
摘要
Abstract
In order to improve the prediction ability of gas emission in mining face,a prediction model based on gate recurrent unit(GRU)is proposed to predict the gas emission by using the relevant influencing factors of gas emission.The initialization process of the sparrow search algorithm is improved,and the improved sparrow algorithm is used to optimize the hyper parameters affecting the GRU prediction model,so as to improve the prediction accuracy of gas emission.Combined with the adaptive enhancement ability of AdaBoost algorithm,an adaptive enhanced optimization gas emission prediction model(ISSA-GRU-AdaBoost model)is constructed,and the prediction index features are extracted by using principal component analysis to improve the rapidity of prediction.The model is compared with PSO-ELM model,QPSO-LSTM model,PSO-BP model and SSA-SVM model.The results show that the prediction accuracy of ISSA-GRU-AdaBoost prediction model is higher.关键词
瓦斯涌出量/预测模型/门控循环单元/麻雀搜索算法/AdaBoost算法/自适应增强优化Key words
gas emission/forecast model/gate recurrent unit/sparrow search algorithm/AdaBoost algorithm/adaptive enhancement optimization分类
矿业与冶金引用本文复制引用
杨超,周文铮,刘雨竹..自适应增强优化的瓦斯涌出量预测模型[J].辽宁工程技术大学学报（自然科学版）,2023,42(6):733-739,7.基金项目
国家自然科学基金项目(51974151 （）
71771111) （）
