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Analysis and Forecast of Urban Air Quality Based on BP Neural Network

International Journal of Advanced Network, Monitoring and Controls
Volume 5 (2020): Issue 3 (January 2020)
By:
Open Access
|Oct 2020

Figures & Tables

Figure 1.

BP neural network learning process
BP neural network learning process

Figure 2.

Log-sigmiod function
Log-sigmiod function

Figure 3.

ReLU function
ReLU function

Figure 4.

Comparison of sample prediction results with real values
Comparison of sample prediction results with real values

COMPARISON BETWEEN MEASURED AND PREDICTED

AQIAQI predictionPM2.5PM 10So2No2CoO3
4556.2127404240.7175
4960.5123476360.6384
5564.3033576350.6284
5768.5439605400.7156
6880.2240675390.7785
6174.3533696470.7071
DOI: https://doi.org/10.21307/ijanmc-2020-028 | Journal eISSN: 2470-8038
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Language: English
Page range: 57 - 64
Published on: Oct 14, 2020
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
AQI,
Air quality Prediction,
BP Neural Network
Related subjects:
Computer sciences,
Computer sciences, other

© 2020 Wenjing Wang, Shengquan Yang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution 4.0 License.

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