Land-sea integrated suitability evaluation of underground space based on Pythagorean fuzzy Bayesian network

Abstract

Scientific development and utilization of urban underground space is an inevitable choice for sustainable urban development. However, in the previous suitability evaluation of underground space in coastal cities, the development potential of underground space in the sea area is not considered. Therefore, this study takes the coastal zone of Jiaozhou bay as the study area, establishes evaluation index systems for land and sea areas separately, and explores a new model for evaluating the suitability of underground space in coastal cities by integrating land and sea. In addition, an underground space suitability evaluation model based on the integration of Pythagorean fuzzy sets and Bayesian network is proposed. Firstly, the Pythagorean triangular fuzzy numbers are used to expand the fuzzy range of expert opinions. Then the Pythagorean triangular fuzzy hybrid geometric operator is used to realize the aggregation of expert opinions to solve the difficulty of obtaining the node conditional probability table by the traditional Bayesian network model of underground space suitability evaluation. Finally, the Pythagorean fuzzy Bayesian network is used as an evaluation tool to carry out the underground space suitability evaluation. Based on the evaluation result and urban planning, the overall planning and functional zoning guidelines for underground space development in the study area are given and the suitability and engineering construction difficulty analysis on the second subsea tunnel of Jiaozhou bay is conducted. The research results can provide a valuable reference for the coastal city planning department to develop and utilize underground space.

Keywords

Underground space / Land-sea integration / Pythagorean fuzzy sets / Suitability evaluation / Bayesian network model

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Xinyu Liu: Methodology, Writing - original draft. Hongjun Liu: Investigation, Data curation. Jie Dong: Project administration, Validation. Peng Yu: Conceptualization, Visualization. Honghua Liu: Investigation, Data curation. Guanghua Cheng: Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements (Grant No. 2024KFKT017) and the Open Foundation of Key Laboratory of Geological Disaster Risk Prevention and Control of Shandong Provincial Emergency Management Department (Grant No. 801KF2024-DZ07)

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