Sustainability evaluation of urban large-scale infrastructure construction based on dynamic fuzzy cognitive map

Abstract

Enhancing the sustainability of large-scale infrastructure construction is the foundation and trend of urban sustainable development and environmental protection. This paper proposes a perception and evaluation method based on Dynamic Fuzzy Cognitive Mapping (D-FCM) to address the dynamics, uncertainties, and implementation difficulties of sustainability evaluation in large-scale infrastructure construction. Using Hebbian rules to learn the experience and knowledge of experts, a dynamic evolution correlation matrix about evaluation indicators is obtained, and a D-FCM dynamic system model is established to obtain the sustainability evaluation results of large-scale infrastructure construction. The comprehensive sustainable evaluation value (K) of the selected subway project case is 0.934, which belongs to the V level in the sustainable level classification standard and has a good trend in sustainable development. Social public participation (S1), light pollution prevention (H1), wastewater discharge compliance rate (H2), soil pollution prevention (H3), and soil and water conservation and utilization (Z2) are the most significant and sensitive indicators for the sustainable development of large-scale infrastructure construction. Based on the interaction of influencing factors in the D-FCM model, an economically efficient control measures and decision-making plan can be proposed to improve the sustainability of large-scale infrastructure construction projects.