关键词: 煤与瓦斯突出, 应急救援能力, 评估模型, 麻雀搜索算法(SSA), 支持向量机(SVM), 组合赋权

Abstract:

In order to reduce the casualties and property losses and improve the emergency rescue capability in coal and gas outburst accidents, an SSA optimized SVM was proposed to evaluate the emergency rescue capability of coal and gas outburst accidents. First, according to relevant literature and research reports, four first-level indicators, including emergency prevention ability, emergency preparedness ability, emergency response ability and recovery and rehabilitation ability, were constructed. These indicators were further subdivided into 18 second-level indicators, and the score data of each indicator was used as the model training dataset. Then, the network analytic Hierarchy process (ANP) and entropy weight method (EWM) were used to determine the subjective and objective weights of each evaluation indicator under the mutual influence, and the Lagrange function was used to merge the weights to obtain the optimal weights. SSA optimized the radial basis parameters g and penalty factor C of SVM. The result of optimal weight calculation was used as the input of the SSA-SVM model, and the expected value was used as the output for linear regression prediction. Finally, taking a mine in Hebei Province as an example, the prediction results of the SSA-SVM model was compared with the traditional SVM, particle swarm optimization algorithm (PSO) optimization SVM and Whale optimization algorithm (WOA) optimization SVM, and the predicted results and the expected values were analyzed. The results show that the prediction results of the SSA-SVM model are consistent with the reality, and the average absolute error decreases by 8.04%, 5.15% and 4.82%, respectively, compared with other models, which proves the superiority of the proposed model. This model can be applied to the evaluation of the emergency rescue ability of coal and gas outburst accidents in actual mines.

Key words: coal and gas outburst, emergency response capability, assessment model, sparrow search algorithm (SSA), support vector machine (SVM), combinatorial assignment