Research on Geological Safety Evaluation Index Systems and Methods for Assessing Underground Space in Coastal Bedrock Cities Based on a Back-Propagation Neural Network Comprehensive Evaluation–Analytic Hierarchy Process (BPCE-AHP)

Abstract

With the rapid development of the economy in China, the scale and quantity of urban underground space development continue to grow rapidly; as such, geological safety problems in urban underground space development and utilization are a research hotspot at present. Therefore, it is important to establish a high-quality evaluation index system and method for assessing the geological safety of urban underground spaces in coastal bedrock. Taking the typical area of Qingdao as an example, this study establishes an effective system for evaluating the geological safety of urban underground space according to the geological background, hydrogeology, engineering geology, and unfavorable geological phenomena in the Hongdao Economic Zone of Qingdao. Then, the method of evaluating the geological safety of urban underground space was studied. Through a comprehensive analysis and comparison of the fuzzy comprehensive evaluation–analytic hierarchy process (FCE-AHP), the grey relation comprehensive evaluation–analytic hierarchy process (GRCE-AHP), the matter-element comprehensive evaluation–analytic hierarchy process (MECE-AHP), and the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP), it was determined that the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP) was an ideal method for evaluating the geological safety of underground space in Qingdao’s coastal bedrock area. This method was used to evaluate the geological safety of the study area, and the evaluation results were verified; this further proved the practicability and rationality of the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP).