[1]ZHOU Shanshan,LI Wenjing,QIAO Junfei.Prediction of PM2.5 concentration based on self-organizing recurrent fuzzy neural network[J].CAAI Transactions on Intelligent Systems,2018,13(4):509-516.[doi:10.11992/tis.201710007]
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Prediction of PM2.5 concentration based on self-organizing recurrent fuzzy neural network

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 4 Page number: 509-516 Column: 学术论文—机器学习 Public date: 2018-07-05
Title:
Prediction of PM2.5 concentration based on self-organizing recurrent fuzzy neural network
Author(s):
ZHOU Shanshan1; 2;  LI Wenjing1; 2;  QIAO Junfei1; 2
1. Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China;
2. Beijing Key Laboratory of Computational Intelligent System, Beijing 100124, China
Keywords:
PM2.5; prediction; PCA; recurrent fuzzy neural network; self-organizing; adaptive gradient descent algorithm
CLC:
TP18
DOI:
10.11992/tis.201710007
Abstract:
To address the nonlinear dynamic variation in the concentration of fine particulate matter (PM2.5), in this paper, we propose a novel self-organizing recurrent fuzzy neural network (SORFNN) for predicting the hourly PM2.5 concentration. First, we analyzed the factors affecting PM2.5 concentration by principal component analysis to identify the characteristic variables and used them as input variables in the neural network. Next, we added or deleted a nerve cell to the regularized layer, based on the ε criterion and partial least squares algorithm, to automatically adjust the recurrent fuzzy neural network. In addition, we applied the adaptive gradient descent algorithm to adjust parameters such as the centers, widths and weights to establish a PM2.5 model. Lastly, to verify the results, we conducted experiments in typical nonlinear system identification and actual PM2.5 concentration prediction. The experimental results show that the proposed SORFNN is compact in structure, has high prediction accuracy, and can satisfy the real-time prediction requirements of PM2.5 concentration.
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