Research on air quality prediction based on BP neural network

Pengyou Lai; LeXi Liu; JingTao Yang

doi:10.1117/12.2626535

21 December 2021 Research on air quality prediction based on BP neural network

Pengyou Lai, LeXi Liu, JingTao Yang

Proceedings Volume 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021); 121561F (2021) https://doi.org/10.1117/12.2626535
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 2021, Sanya, China

Abstract

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.

Citation Download Citation

Pengyou Lai, LeXi Liu, and JingTao Yang "Research on air quality prediction based on BP neural network", Proc. SPIE 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 121561F (21 December 2021); https://doi.org/10.1117/12.2626535

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available