A Novel Evaluation Model of Subway Station Adaptability Based on Combination Weighting and an Improved Extension Cloud Model

The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering the construction and operation phases are selected by a literature review, providing a basis for planning decision makers. The Projection Pursuit Method (PPM) and the Bald Eagle Search (BES) algorithm are employed to assign objective weights. The Continuous Ordered Weighted Averaging (COWA) operator is utilized to obtain subjective weights. A combination weighting method is used based on game theory to improve the accuracy of weight calculation. Game theory and extension cloud theory are applied to develop an improved extension cloud model and evaluate the suitability based on optimal cloud entropy. We conduct a case study of 15 stations on the Chengdu Metro Line 11, China. The results reveal that the coordination of the development plans, the alignment with the land use plan, and regional population density are the most crucial tertiary indicators that should be considered in selecting subway station locations. These findings agree with the actual conditions, demonstrating the scientific validity of the proposed evaluation method, which outperforms classical evaluation methods. The proposed method is efficient and feasible for selecting subway station locations.

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