###### Abstract
These countries have invested in research and development to find innovative solutions for treating and managing mine water to protect the environment and public health. Mine water damage management has long been a critical area of research in mining. Various countries have extensively explored and implemented strategies to evaluate the effectiveness of grouting in managing mine water damage [5; 6]. Numerical simulation techniques have been widely adopted by researchers to predict grouting outcomes. By constructing geological and numerical models, these simulations replicate the slurry diffusion and strata deformation during the grouting process, enabling predictions of potential water damage post-grouting. For instance, methods like the finite element method and finite difference method have been employed to analyze the stress, displacement, and seepage fields of strata following grouting, facilitating the assessment of grouting effectiveness [7; 8; 9; 10]. Furthermore, real-time monitoring of parameters such as water level, pressure, and flow rate is achieved by installing monitoring devices like water level gauges, pressure sensors, and flow meters [11; 12]. The collected data is then processed using statistical techniques, such as regression and time series analyses, to evaluate the grouting treatment's efficacy [13]. Several studies have relied on single evaluation methods, such as the analytic hierarchy process (AHP) [14; 15; 16], grey relational analysis [17; 18], and fuzzy comprehensive evaluation [19; 20], to assess grouting management outcomes. While these approaches capture certain aspects of the grouting process, they are not without limitations. For instance, AHP is often criticized for its subjectivity, as the results may be influenced by the personal biases of experts. Grey relational analysis demands highly stable data, and significant fluctuations can compromise accuracy. Fuzzy comprehensive evaluation involves complex calculations, and its resolution may lack precision. To address the shortcomings of singular approaches, scholars have explored combining evaluation methods. For example, AHP, fuzzy comprehensive evaluation, and grey relational analysis have been integrated to provide a more holistic assessment of grouting effectiveness by considering multiple evaluation indices. In constructing a grouting evaluation index system, researchers have dedicated significant effort to developing comprehensive frameworks [21; 22; 23; 24]. Typically, these systems incorporate various indicators such as grouting volume, pressure, water level variation, strata deformation, and water quality changes. Different evaluation index systems have been formulated based on specific research objectives. However, challenges persist, including insufficient comprehensiveness in indicator selection and a lack of scientific rigor in determining indicator weights. As previously noted, relying on a single evaluation method presents inherent limitations. For instance, the AHP is prone to subjectivity, grey relational analysis demands stringent data conditions, and the fuzzy comprehensive evaluation method involves complex calculations. These challenges hinder the ability of a singular method to deliver accurate and comprehensive assessments of mine water damage grouting management in practical applications. A critical issue within evaluation index systems is the determination of indicator weights. Currently, the most commonly employed approaches are subjective and objective assignment methods. The subjective assignment method relies heavily on expert judgment and experience, leading to potential bias due to individual subjectivity. Conversely, the objective assignment method determines weights based on the statistical properties of the data, offering greater objectivity but often overlooking the real-world significance of certain indicators. Thus, there is a pressing need to develop a more scientific and balanced approach to determining indicator weights.