Apply Genetic Algorithm to Cloud Motion Wind

  • Jiang Han
  • Ling Li
  • Chengcheng Yang
  • Hui Tong
  • Longji Zeng
  • Tao Yang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 260)

Abstract

Cloud Motion Wind (CMW) is a very important issue in the meteorology. In this paper, we firstly apply Genetic Algorithm (GA) to the CMW searching to reduce the computational complexity. We propose a novel CMW method, namely GA-CMW. Compared with the traditional Exhaustive CMW (E-CMW) algorithm, GA-CMW can obtain almost the same performance while with only 11 % of the computational complexity required. Generally speaking, the proposed GA-CMW method can obtain the wind vector picture in shorter time, which makes a lot of sense to the resource saving in the practical application.

Keywords

Image matching Cloud motion wind Genetic algorithm Cross-correlation coefficient Computational complexity 

Notes

Acknowledgments

This paper is supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China under Grand 2012ZX03001039-002, which is kindly acknowledged.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Jiang Han
    • 1
  • Ling Li
    • 2
  • Chengcheng Yang
    • 1
  • Hui Tong
    • 3
  • Longji Zeng
    • 4
  • Tao Yang
    • 4
  1. 1.Key Laboratory of Universal Wireless Communications, Ministry of EducationBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.College of Mathematic and InformationChina West Normal UniversitySichuanChina
  3. 3.School of ScienceBeijing University of Posts and TelecommunicationsBeijingChina
  4. 4.School of Electronic and Information EngineeringBeijing Jiaotong UniversityBeijingChina

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