JOURNAL ARTICLE

URBAN CLASSIFICATION BASED ON RANDOM FOREST ALGORITHM

Peng Lin and Lixin Yang

Year: 2019 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

This paper discussed the research content from five parts. The first chapter mainly introduced the background and significance of the research and the research status at home and abroad. The second chapter introduced the theoretical knowledge and implementation of the research method, namely the random forest algorithm. The third chapter introduced the index system of city classification.The fourth chapter introduced the establishment of stochastic forest algorithm model and discusses the feasibility of the model from the model results. The fifth chapter made a summary of the whole thesis.

Keywords:
Random forest Computer science Geography Artificial intelligence Remote sensing Algorithm

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Topics

Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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