A novel prediction model of PM2.5 mass concentration based on back propagation neural network algorithm-Reference-Cited by-同舟云学术

A novel prediction model of PM2.5 mass concentration based on back propagation neural network algorithm

Published:2019-10-09 Issue:3 Volume:37 Page:3175-3183
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Chen Yegang¹,An JianMei²,Yanhan ³

Affiliation:

1. College of Big Data and Intelligent Engineering, Yangtze Normal University, Fuling, Chongqing, China

2. Chongqing University of Arts and Sciences, Yongchuan, Chongqing, China

3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference30 articles.

1. A conjunction method of wavelet transform-particle swarm optimization-support vector machine for streamflow forecasting;Zhang;Journal of Applied Mathematics

2. Evolutionary energy balanced ant colony algorithm based on WSNs;Chen;Cluster Computing

3. Modeling the concentration of pollutants using the WRF-ARW atmospheric model and CHIMERE chemistry transport model;Zaripov;Russian Meteorology & Hydrology,2013

4. Household concentrations and personal exposure of PM 2.5, among urban residents using different cooking fuels;Li;Science of the Total Environment

5. Response by Li et al to letters regarding article, particulate matter exposure and stress hormone levels: A randomized;Li;Double-Blind, Crossover Trial of Air Purification, Circulation,2018

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