Open Access

ARTICLE

GA-BP Air Quality Evaluation Method Based on Fuzzy Theory

Ma Ning^1,*, Jianhe Guan¹, Pingzeng Liu², Ziqing Zhang³, Gregory M. P. O’Hare⁴

1 China University of Geoscience, Beijing, 100083, China.
2 Shandong Agricultural University, Taian, 271018, China.
3 Shandong Vocational Institute of Fashion Technology, Taian, 271000, China.
4 University College Dublin (UCD), Belfield, Dublin, 999014, Ireland.

* Corresponding Author: Ma Ning. Email: .

Computers, Materials & Continua 2019, 58(1), 215-227. https://doi.org/10.32604/cmc.2019.03763

Abstract

With the rapid development of China’s economy, the scale of the city has been continuously expanding, industrial enterprises have been increasing, the discharge of multiple pollutants has reached the top of the world, and the environmental problems become more and more serious. The air pollution problem is particularly prominent. Air quality has become a daily concern for people. In order to control air pollution, it is necessary to grasp the air quality situation in an all-round way. It is necessary to evaluate air quality. Accurate results of air quality evaluation can help people know more about air quality. In this paper, refers to previous research results and different evaluation methods, combined with artificial neural network, fuzzy theory, genetic algorithm, GA-BP hybrid algorithm based on fuzzy theory is proposed to evaluate air quality. At the same time, for the problem that the two-grade standard of air quality annual evaluation is not suitable for practical application, the four-grade standard for annual air quality evaluation has been proposed, and its practicality has been verified through experiments. By setting contrast experiments and comparing the air quality evaluation model based on standard BP algorithm, it is proved that the fuzzy GA-BP evaluation model is better than the standard BP model, both in efficiency and accuracy.

---

Keywords

---

Citations