Risk identification of coal and gas outburst based on improved CUOWGA weighting TOPSIS model.

In order to accurately assess the risk level of coal and gas outbursts, this study proposes an evaluation method based on an improved CUOWGA-weighted TOPSIS model. The primary challenge faced in evaluating the risk of coal and gas outbursts is the subjectivity of the evaluation indicators, which may lead to unreliable outcomes. To address this issue, a coal and gas outburst evaluation indicator system comprising three key factors-geological conditions, coal seam gas content, and the physical properties of coal and rock-was constructed based on an extensive review of the literature. By introducing an innovative fuzzy semantic quantification operator and a normalized decision matrix, the computation process of the CUOWGA operator is optimized to minimize subjective bias and appropriately allocate weights to the evaluation indicators. By combining the optimized CUOWGA method with TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), the risk level of coal and gas outbursts was assessed. A case study conducted at Duanshi Coal Mine demonstrated that the risk level of coal and gas outbursts at this mine is classified as Level II, which is consistent with the actual conditions observed in the mining area. These results validate that the evaluation method based on the ICUOWGA-weighted TOPSIS model can effectively assess the risk level of coal and gas outbursts, thereby proving the feasibility of the approach.