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Academic Journal of Computing & Information Science, 2022, 5(9); doi: 10.25236/AJCIS.2022.050901.

Study on Urban Rainfall Trend Based on Neural Network and Grey Correlation Analysis Model

Author(s)

Yi Wu1, Lei Huang2, Anqi Chen1, Cai Chen1

Corresponding Author:
Yi Wu
Affiliation(s)

1School of Automotive and Traffic Engineering, Hubei University of Arts and Sciences, Hubei, China

2College of Science, Liaoning Technical UniversitFux, Liaoning, China

Abstract

This paper is based on a quantitative analysis of the 2021 flood event in Zhengzhou City. The precipitation data of more cities in China are collected and compiled for many years, and the precipitation trends of the cities they collect are analyzed. It also collects weather data from more cities, uses various methods to forecast and analyze cities that may experience extreme rainfall in the future, and compares and analyzes the forecast results.

Keywords

Quadratic exponential smoothing method; LSTM neural network model; Elm Algorithm

Cite This Paper

Yi Wu, Lei Huang, Anqi Chen, Cai Chen. Study on Urban Rainfall Trend Based on Neural Network and Grey Correlation Analysis Model. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 9: 1-6. https://doi.org/10.25236/AJCIS.2022.050901.

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