论文信息 - A Piecewise Linearization Method of Significant Wave Height Based on Particle Swarm Optimization

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

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.

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