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A Piecewise Linearization Method of Significant Wave Height Based on Particle Swarm Optimization

  • Liqiang Liu
  • Zhichao Fan
  • Xiangguo Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7928)

Abstract

A piecewise linearization method of significant wave height is proposed based on particle swarm optimization. Piecewise linearization model is used to approximate significant wave height inversion model, minimum radius of neighborhood is used to eliminate wild value in the sample data and sparse the data, and then the particle swarm optimization algorithm is applied for piecewise area division and parameter optimization of the model. Simulation result shows that compared with traditional inversion method, better practicability and the higher significant wave height inversion precision are obtained by the proposed method.

Keywords

particle swarm optimization significant wave height piecewise linearization X-band radar 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Liqiang Liu
    • 1
  • Zhichao Fan
    • 1
  • Xiangguo Wang
    • 1
  1. 1.College of AutomationHarbin Engineering UniversityHarbinChina

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