Using XGBoost, SHAP, and counterfactual explanations, the study generates minimal building-height and setback changes that improve Sky View Factor and visibility in synthetic urban blocks with 4 to 6 percent average simulation error.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
An AI-driven framework for rapid and localized optimizations of urban open spaces
Using XGBoost, SHAP, and counterfactual explanations, the study generates minimal building-height and setback changes that improve Sky View Factor and visibility in synthetic urban blocks with 4 to 6 percent average simulation error.