Coal seam gas emission quantity prediction method based on SSA-CIRCLE-ELM model

The invention discloses a coal seam gas emission quantity prediction method based on an SSA-CIRCLE-ELM model, and belongs to the technical field of gas prediction. The method comprises the following steps: initializing a search space of a sparrow search algorithm by utilizing CIRCLE chaotic mapping; using a sparrow search algorithm to optimize SLFN nodes of the extreme learning machine, and enabling parameters of the SLFN nodes to generate continuous probability distribution; constructing a multi-dimensional state matrix, and carrying out feature mapping on the multi-dimensional state matrix by using an extreme learning machine and minimizing an error function of the multi-dimensional state matrix; and predicting the gas data by using the optimized extreme learning machine. According to the coal seam gas emission quantity prediction method, the SSA-CIRCLE-ELM model can be constructed. 本发明基于SSA-CIRCLE-ELM模型的煤层瓦斯涌出量预测方法，属于瓦斯预测技术领域。本发明方法包括：利用CIRCLE混沌映射对麻雀搜索算法的搜索空间进行初始化；再使用麻雀搜索算法优化极限学习机的SLFN节点，使其参数生成连续概率分布；构建多维状态