Research on air quality prediction based on BP neural network

被引：0

作者：

Lai, PengYou ^{[1
]}

Liu, LeXi ^{[1
]}

Yang, JingTao ^{[2
]}

机构：

[1] Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang 524088, Guangdong, Peoples R China

[2] Guangdong Ocean Univ, Coll Math & Comp Sci, Zhanjiang 524088, Guangdong, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON ALGORITHMS, HIGH PERFORMANCE COMPUTING, AND ARTIFICIAL INTELLIGENCE (AHPCAI 2021) | 2021年 / 12156卷

关键词：

Air quality; Neural network; PSO-GA hybrid algorithm; Prediction;

D O I：

10.1117/12.2626535

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Air quality is affected by different geographic conditions, human activities, and it depends on an atmospheric environment that is a complex, high-dimensional, large system influenced by multiple feature factors and intricate relationships among them, so it has extremely significant nonlinear characteristics. In this paper, we use BP neural networks in machine learning algorithms to conduct research on air quality prediction, in which we mainly use a BP neural network model with an improved PSO-GA hybrid algorithm. The model is good at dealing with nonlinear problems, has strong noise tolerance, and its prediction results have strong applicability.

引用

页数：6

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