# An Integrated Decision Support System for Low-Disturbance Surface Mining
## 5 Conclusions  
The primary conclusions are as follows:  
1. A decision support system for low-disturbance mining in open pit mines is proposed to provide key technical support for low-disturbance mining in open pit mines to promote the development of low-disturbance mining in open pit mines. To consider the impact of different mine works, two frameworks, low-disturbance open pit mining challenge and low-disturbance open pit mining path, were constructed in the decision support system. The Low Disturbance Surface Mining Challenge Framework involves 4 leading indicators and 13 sub-indicators. The Mining Pathways Framework consists of 4 main technology pathways. 2. Based on the fuzzy hierarchical analysis method, the weights of all indicators were determined and ranked, and the grey clustering method based on the centroid triangular whitening weight function was used to evaluate the indicators. The study shows that the level of low-disturbance mining in open-pit mines is low at this stage and that all indicators need to be attended to and corresponding measures taken immediately. The leading indicators to focus on and study are \"Control of stripping works (CS)\" and \"Control of pollution emission (CP)\". The sub-indicators \"Stripping intensity (CS2)\", \"Utilisation of inner dump (CE3)\" and \"Emission intensity of gaseous pollutants (CP3)\" need to be emphasized, and corresponding measures are taken promptly. 3. The F-TOPSIS method is used to calculate the comparative advantages of the four possible paths. For the current stage of China's open pit mine LDM development, the optimal path ordering under each leading indicator is given respectively, which provides optimal decision-making for the development of low-disturbance open pit mines. Comprehensive studies have shown that the prioritization of optimal paths to achieve a low-disturbance open pit mine is \"Optimised design (OD)\" > \"Intelligent dispatch (ID)\" > \"Land reclamation (LR)\" > \"Optimisation of processes (OP)\". All authors contributed to this study. [PERSON] and [PERSON] designed the research study. [PERSON] analyzed the field data. [PERSON] wrote this paper. [PERSON] reviewed the manuscript. [PERSON] guided the research procedures and reviewed them. All authors gave final approval for publication. All authors have read and agreed to the published version of the manuscript. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Not applicable. The data that support the findings of this study are available from the corresponding author, [[PERSON]], upon reasonable request. The authors declare no conflicts of interest. \begin{table}
\begin{tabular}{c c c c c} \hline Reality & CPI & CP2 & CP3 & CP4 \\ \hline CP1 & (1, 1, 1) & (1.0095, 1.7092, 2.4820) & (1.6364, 2.3893, 3.0536) & (1.0366, 1.3957, 1.7955) \\ CP2 & (0.5157, 0.5652, 0.8717) & (1, 1.1) & (1.7294, 2.4495, 3.1654) & (1.7692, 2.4656, 3.463) \\ CP3 & (0.3275, 0.4299, 0.6111) & (0.3159, 0.4082, 0.5782) & (1, 1.1) & (1.4738, 1.8892, 2.3889) \\ CP4 & (0.5837, 0.6811, 0.9467) & (0.2910, 0.3780, 0.5652) & (0.4191, 0.3780, 0.5676) & (1, 1.1) \\ \hline Desurability & CPI & CP2 & CP3 & CP4 \\ \hline CP1 & (1, 1, 1) & (1.0036, 1.7087, 2.4137) & (1.5786, 2.2944, 2.9848) & (1.0366, 1.2799, 1.3651) \\ CP2 & (0.5030, 0.5859, 0.9170) & (1, 1, 1) & (1.5868, 2.1352, 2.6618) & (1.6224, 2.3061, 2.8899) \\ CP3 & (0.3350, 0.4388, 0.6335) & (0.3757, 0.4686, 0.6306) & (1, 1, 1) & (1.2864, 1.5858, 1.9511) \\ CP4 & (0.6164, 0.7427, 0.8245) & (0.3461, 0.4336, 0.6164) & (0.5125, 0.6306, 0.7747) & (1, 1, 1) \\ \hline \end{tabular}
\end{table} 
Table 4: Pairwise comparison of sub-indicators under control of pollution emission (CP).