Abstract
Decision making are critical for disaster prevention and emergency response. To fully improve the effectiveness of emergency decisions by taking spatiotemporal information into consideration, this paper proposes a new method STGA-CBR for spatiotemporal case matching by using an integrated approach comprising a newly proposed spatiotemporal trajectory similarity measurement algorithm (Position-Frequency algorithm), a genetic algorithm (GA), and a case-based reasoning (CBR) technique. It consists of three main phases: (1) similar spatiotemporal trajectory retrieval; (2) weight determination; and (3) attribute similarity calculation. The proposed approach was employed in typhoon disaster, which contains a variety of spatiotemporal information. The results of matching were validated by comparing STGA-CBR with ST-CBR, GA-CBR and traditional simple CBR. The experimental results proved that the proposed STGA-CBR effectively screens out similar spatiotemporal trajectories and demonstrates higher matching performance than there other methods, indicating the high efficiency of the proposed similar case retrieval approach. The case pair selected are then used for prediction of the post-disaster social and economic loss and the average accuracy of prediction results are calculated, among which the integrated model rank the highest, thus rendering our approach superior in comparison to other traditional methods.
Highlights
In recent years, various disasters and emergencies have occurred frequently in the world
Aiming at problems introduced above, this paper focuses on typhoon, a typical natural disaster with long duration, wide range of influence and rich information of space-time trajectory, as the research object, and proposes a STGA-Case-Based Reasoning (CBR) method based on time-space trajectory similarity measure and genetic algorithm
The experimental results prove that compared with the traditional CBR method that only considers the attribute information such as the property loss and typhoon intensity, the case matching result obtained by combining the spacetime information is more accurate, and can serve the relevant prediction of the post-disaster social and economic loss, thereby assisting the relevant departments response timely, dispose reasonably, and react effectively during the disaster emergency
Summary
Various disasters and emergencies have occurred frequently in the world. Aiming at problems introduced above, this paper focuses on typhoon, a typical natural disaster with long duration, wide range of influence and rich information of space-time trajectory, as the research object, and proposes a STGA-CBR method based on time-space trajectory similarity measure and genetic algorithm. Based on the typhoon case with similar time-space attributes retrieved by Position-Frequency algorithm, a spatiotemporal trajectory similarity measurement algorithm, the final similar case matching result are obtained by using the AHP-GA and the case attribute similarity calculation method. The experimental results prove that compared with the traditional CBR method that only considers the attribute information such as the property loss and typhoon intensity, the case matching result obtained by combining the spacetime information is more accurate, and can serve the relevant prediction of the post-disaster social and economic loss, thereby assisting the relevant departments response timely, dispose reasonably, and react effectively during the disaster emergency. By setting the parameters such as crossover probability and mutation probability, the optimal weight is calculated
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