Learning to Optimise Climate Sensor Placement using a Transformer

arXiv:2310.12387v2 Announce Type: replace
Abstract: The optimal placement of sensors for environmental monitoring and disaster management is a challenging problem due to its NP-hard nature. Traditional methods for sensor placement involve exact, approximation, or heuristic approaches, with the latter being the most widely used. However, heuristic methods are limited by expert intuition and experience. Deep learning (DL) has emerged as a promising approach for generating heuristic algorithms automatically. In this paper, we introduce a novel sensor placement approach focused on …

abstract approximation arxiv climate cs.ai cs.lg disaster disaster management environmental expert however management monitoring nature np-hard placement sensor sensors transformer type