Karst collapse, a sudden geological hazard with complex mechanisms and low predictability, presents significant threats to urban safety and sustainable development by jeopardizing human lives and infrastructure. To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. The methodology incorporates two key innovations: first, it applies a Singer ...
