Investment estimation of urban renewal projects based on case-based reasoning

Against the background of accelerating urbanisation, urban renewal plays a critical role in urban development and spatial-quality improvement. Large-scale urban renewal practices worldwide still lack mature investment-estimation tools, and few studies introduce case-based reasoning (CBR) into urban renewal investment forecasting. To fill this gap, this study develops a CBR model integrated with grey relational analysis for urban renewal project investment estimation. Nine key characteristic indicators are identified from policy and literature analysis, whose weights are calculated using the analytic hierarchy process-criteria importance through intercriteria correlation combined weighting method. A case library containing 45 Chinese urban renewal projects across seven geographical regions is established. Validated by nine target cases and compared with traditional methods, the model's predicted unit investment estimation achieves a mean absolute percentage error of 4.94%, with better accuracy and stability than traditional approaches. This model overcomes the limitations of traditional methods, improves estimation efficiency, and provides reliable decision support for the early-stage investment planning of urban renewal projects.