Intelligent Reasoning and Decision‐Making in Disaster Scenarios

Disasters, in the recent past, have become a frequently occurring cause for the destruction of mankind and have a huge impact on socioeconomic development. And, decision-making in such destructive scenarios stands crucial as it influences the disaster impact and decreases the losses during the disaster scenarios. This work undertakes comprehensive exploration of the role of intelligent reasoning in decision-making during disaster scenarios. According to the decision-making possibility, the disaster scenarios are broadly categorized as three pivotal phases: disaster prediction, disaster impact, and precautionary measures. The study traced that various learning techniques have been considered and used to make an “effective” decision. Both deep learning and machine learning methods provide a strong and convincing sense of reasoning and make the systems yield effective decisions. It has been proven many times that intelligent reasoning paves the way for logic-based derivation toward concluding on a loss-effective decision. The work stands as a source for a meticulous examination of various disasters such as earthquakes, floods, landslides, cyclones, and droughts in various phases of decision-making, including its analysis of intelligent reasoning.