Research on Decision Support for Basic Class Reconstruction in Old Residential Areas Based on Case-Based Reasoning and Utility Theory

The basic renovation of old urban communities is an important livelihood project for urban renewal, but there are many problems in the decision-making of renovation schemes, such as strong dependence on experience, lack of quantitative basis for multi-objective trade-off, and difficulty in describing residents’ risk attitude. Combining Case-Based Reasoning (CBR) and utility theory, this paper constructs a set of intelligent decision support models driven by data and knowledge. First of all, through literature analysis and expert investigation, a decision-making index system is established, which includes four dimensions and 16 quantitative indicators: policy and financial support, residential conditions and needs, residents’ consensus and social coordination, and implementation management and long-term maintenance. Secondly, the framework representation method is used to describe the reconstruction case, a hybrid retrieval strategy combining inductive retrieval and nearest-neighbor retrieval is designed, and the subjective and objective data combination weights are calculated by using AHP and the entropy method. On this basis, a loss utility function and risk aversion coefficient based on accident and public opinion data (a = 0.02) are introduced to modify the similarity calculation results to describe the risk avoidance behavior of decision-makers. Through 40 real renovation projects, a case base is built, and two types of target cases, “typical inclusive” (F5) and “key renovation” (F35), are selected for empirical verification. The results show that the model can effectively retrieve similar cases, and the similarity ranking changes in line with risk aversion expectations after utility correction. Taking F5 as an example, by reusing and revising the reconstruction scheme of a similar case, targeted suggestions are generated, which give consideration to safety, economy and operability. This model provides a new quantifiable and reusable method for scientific decision-making in basic renovation of old residential areas.