WCSE

A Novel Adaptive Resource Allocation Framework for Sounding Networks

Abstract— For a long time, the detection of meteorological data is very important for weather prediction. However, in the process of data detection, manual input is often tedious and data duplication is easy to be lost, which is not conducive to the acquisition of meteorological data. To solve this problem, this paper presents a novel framework for the adaptive allocation of sounding network resources and uses a genetic algorithm and simulated annealing algorithm method to optimize the processing of meteorological data. Experimental results based on real data sets show that the method proposed in this paper improves the efficiency of data processing, simplifies the manual operation, and improves the accuracy of data, which provides a new idea for the processing of meteorological data

Index Terms— genetic algorithm, simulated annealing algorithm, meteorological data

Na Gong
Beijing HY Orient Detection Technology Co., Ltd., CHINA
YinFeng Liu
Beijing HY Orient Detection Technology Co., Ltd., CHINA
Jie Ren
Beijing HY Orient Detection Technology Co., Ltd., CHINA
Qun Wu
Beijing HY Orient Detection Technology Co., Ltd., CHINA
Halei Hu
School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, CHINA

[Download]

Cite: Na Gong, YinFeng Liu, Jie Ren, Qun Wu, Halei Hu , "A Novel Adaptive Resource Allocation Framework for Sounding Networks ," 2021 The 11th International Workshop on Computer Science and Engineering (WCSE 2021), pp. 276-283, Shanghai, China, June 19-21, 2021.