Optimization of ecological and efficient restorati

The geological conditions of mines are complex and diverse, necessitating advanced restoration methods to adequately rehabilitate various mine types. This study introduces an innovative approach for optimizing ecological restoration technologies for green mines using the hesitant fuzzy TOPSIS methodology. A digital terrain model (DTM) is constructed utilizing a remote 3D laser scanner to assess target mines, which are then segmented into zones according to geological characteristics such as lithology, slope aspect, and angle. Eight indicators, including uniaxial saturated compressive strength and rock quality designation, are employed to evaluate the rock mass quality of each slope zone. The approach involves creating a hesitant fuzzy decision matrix based on these indicators, determining their respective weights through a maximum deviation method, and calculating weighted distances to assess each zone against prescribed ideal solutions. The results indicate that using this framework, reclaimed mining slopes can achieve a dust control efficiency significantly superior to traditional methods, with a vegetation restoration rate of 25% in guided/southern zones, whereas other methods yield below 15%. This research underscores the operational efficiency and quality improvements achievable through the proposed technology, ultimately promoting sustainable ecological restoration practices in mining.