Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method
International Journal of Statistical Distributions and Applications
Volume 1, Issue 1, September 2015, Pages: 12-18
Received: Sep. 5, 2015; Accepted: Sep. 16, 2015; Published: Sep. 16, 2015
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Authors
Lu Yadong, Department of Mathematics, Sichuan University, Chengdu, China
Zhou Ya, Department of Mathematics, Sichuan University, Chengdu, China
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Abstract
Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.
Keywords
Optimal Search and Rescue Plan, Dinkelbach's Algorithm, Bayesian Inference, Probability Density Map
To cite this article
Lu Yadong, Zhou Ya, Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method, International Journal of Statistical Distributions and Applications. Vol. 1, No. 1, 2015, pp. 12-18. doi: 10.11648/j.ijsd.20150101.13
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