Weather processes interpolation based on GPR

This project aims at interpolating wind fields. The main idea of it is multi-scale anisotropy kernel, which can extract multi-scale dependencies of weather processes. Weather processes with and without cyclones are discussed, and two interpolation methods are proposed. Check paper for more information. Codes are available here.

Reference

Carl Edward Rasmussen. Gaussian process for Machine Learning.

Acknowledgement

Thanks for the opening source toolbox GAUSSIAN PROCESS REGRESSION AND CLASSIFICATION Toolbox version 4.0, programmed by Carl et al.

tag:

    缺失模块。
    1、请确保node版本大于6.2
    2、在博客根目录（注意不是yilia根目录）执行以下命令：
    npm i hexo-generator-json-content --save

    3、在根目录_config.yml里添加配置： 

      jsonContent:
    meta: false
    pages: false
    posts:
      title: true
      date: true
      path: true
      text: false
      raw: false
      content: false
      slug: false
      updated: false
      comments: false
      link: false
      permalink: false
      excerpt: false
      categories: false
      tags: true

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