An urban coordinated development evaluation method based on water resources and coupling factors

Abstract

This invention provides a method for assessing coordinated urban development based on water resources and their coupling factors, belonging to the field of development evaluation technology based on deep learning. First, this invention constructs a structured dataset covering a three-element system and introduces physical quantitative labels to ensure the objectivity of the assessment results. Second, it designs a causal modeling network with a two-level structure, integrating system-level and indicator-level contribution analysis mechanisms to achieve structured mining of coupled causal relationships. Subsequently, through a model structure inversion mechanism, it proposes a three-dimensional indicator system to assess the potential, coordination, and stability of urban development. Finally, combining structural prior information and assessment results, it constructs a game theory-driven multi-round regulation path deduction framework to achieve automatic generation of synergistic variable regulation schemes and predictive evaluation of development effectiveness, thereby providing cities with high-quality coordinated development path suggestions that are inferable and mechanistically explainable.

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