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A New Searching Strategy for the Lost Plane Based on RBF Neural Network Model and Global Optimization Model
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作者 Yiqing YU 《International Journal of Technology Management》 2015年第4期126-128,共3页
In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF n... In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF neural network model, and then determine the searching area according to the trajectory. With the pass of time, the searching area will also be constantly moving along the trajectory. Model 2 develops a maritime search plan to achieve the purpose of completing the search in the shortest time. We optimize the searching time and transform the problem into the 0-1 knapsack problem. Solving this problem by improved genetic algorithm, we can get the shortest searching time and the best choice for the search power. 展开更多
关键词 the trajectory of floats rbf neural network model Global optimization model 0-1 knapsack problem improved geneticalgorithm
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