Open AccessResearch on the Applicability of Weather Forecast Model—Based on Logistic Regression and Decision Tree
Author(s) -
Feiyang Deng
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1678/1/012110
Subject(s) - logistic regression , decision tree , meteorology , agriculture , weather forecasting , regression analysis , environmental science , computer science , environmental resource management , geography , machine learning , archaeology
With the continuous development of meteorological technology, weather forecast has become an indispensable part of human in agriculture and life. Regardless of whether it is a climate forecast on rainfall in agriculture or a weather forecast on mobile phones or TV, a variety of climate forecasts bring great convenience to people’s production and life. For ordinary people, the prediction of whether it will rain the next day seems to be more practical. Many people determine the clothing and whether to bring an umbrella to go out for the next day by checking the weather forecast on mobile phones and TVs. It can be said that the prediction of rain directly affects people’s living habits. On such basis, this article studies the question of whether it will rain tomorrow in life. Based on about 140,000 meteorological data from the Australian Meteorological Bureau, this article studies and analyzes the influential effect of whether it will rain tomorrow by establishing a logistic regression and decision tree model, and sets up a prediction model to predict whether it will rain tomorrow.