Sensitivity analysis of urban planning using random forests and transformers: a case study of residential area renovation

Currently, residential area renovation in urban planning is facing many problems. Traditional sensitivity analysis methods are often difficult to handle. Therefore, this article proposes a comprehensive method that combines random forest and transformer models. Firstly, the random forest algorithm is used to evaluate the feature importance of multidimensional influencing factors in residential area renovation and identify key influencing factors; subsequently, leveraging the advantages of the transformer model, the complex nonlinear relationships and spatiotemporal dependencies between key factors were processed, improving the accuracy and interpretability of sensitivity analysis. Through empirical analysis, the effectiveness and superiority of this method in sensitivity analysis of residential area renovation have been verified, providing more scientific and accurate decision support for urban planning. Research has shown that the combination of random forest and transformer can provide a new approach for sensitivity analysis in complex planning tasks.