Expanding mining operations in goaf zones heightens gas production potential, posing challenges in maintaining adequate ventilation within development panels, consequently impacting coal production. Various strategies have been explored to enhance mine ventilation and gas drainage effectiveness. However, deficiencies persist in the proposed ventilation system for the Okaba underground coal mine, prompting this study’s necessity. Addressing these concerns, the study evaluates the feasibility of employing booster fans to mitigate the identified drawbacks. Prioritizing booster fans for airflow distribution in underground mines is a complex decision-making process, requiring an advanced expert system approach. To address this, the study proposes an intuitionistic-based fuzzy TOPSIS (IFT) method for booster fan prioritization in the Okaba mine. Results indicate that booster fan 4 (BF4) ranks highest, followed by booster fan 3 (BF3), consistent with fuzzy TOPSIS findings. Sensitivity analysis supports the predicted importance order, affirming the efficacy of the hybrid expert decision method in selecting a booster fan capable of enhancing the overall efficiency of gas drainage and ventilation systems in underground mines. This study introduces a Hybrid Expert Decision Approach that integrates IFT and traditional fuzzy TOPSIS methodologies. This hybrid approach is particularly novel because it combines the strengths of both methods to prioritize booster fans in underground coal mines.

中文翻译：

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提高地下煤矿的瓦斯排放和通风效率：增压风扇优先级的混合专家决策方法


在采空区扩大采矿作业提高了天然气生产潜力，对保持开发板内的充足通风构成了挑战，从而影响了煤炭生产。已经探索了各种策略来提高矿井通风和瓦斯抽放效率。然而，拟议的冈场地下煤矿通风系统仍然存在缺陷，因此有必要进行这项研究。为了解决这些问题，该研究评估了使用增压风扇来减轻已发现的缺点的可行性。在地下矿井中，优先考虑增压风扇进行气流分配是一个复杂的决策过程，需要先进的专家系统方法。为了解决这个问题，该研究提出了一种基于直觉的模糊 TOPSIS （IFT） 方法，用于冈场矿的增压风扇优先级排序。结果表明，增压风扇 4 （BF4） 排名最高，其次是增压风扇 3 （BF3），这与模糊 TOPSIS 结果一致。敏感性分析支持预测的重要性顺序，肯定了混合专家决策方法在选择能够提高地下矿井中瓦斯排放和通风系统整体效率的增压风扇的有效性。本研究介绍了一种混合专家决策方法，该方法集成了 IFT 和传统的模糊 TOPSIS 方法。这种混合方法特别新颖，因为它结合了两种方法的优势，可以优先考虑地下煤矿中的增压风扇。