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Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network
The monitoring-blind area exists in the industrial park because of private interest and limited administrative power. As the atmospheric quality in the blind area impacts the environment management seriously, the prediction and inference of the blind area is explored in this paper. Firstly, the fusi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843783/ https://www.ncbi.nlm.nih.gov/pubmed/31600885 http://dx.doi.org/10.3390/ijerph16203788 |
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author | Bai, Yu-ting Wang, Xiao-yi Sun, Qian Jin, Xue-bo Wang, Xiao-kai Su, Ting-li Kong, Jian-lei |
author_facet | Bai, Yu-ting Wang, Xiao-yi Sun, Qian Jin, Xue-bo Wang, Xiao-kai Su, Ting-li Kong, Jian-lei |
author_sort | Bai, Yu-ting |
collection | PubMed |
description | The monitoring-blind area exists in the industrial park because of private interest and limited administrative power. As the atmospheric quality in the blind area impacts the environment management seriously, the prediction and inference of the blind area is explored in this paper. Firstly, the fusion network framework was designed for the solution of “Circumjacent Monitoring-Blind Area Inference”. In the fusion network, the nonlinear autoregressive network was set up for the time series prediction of circumjacent points, and the full connection layer was built for the nonlinear relation fitting of multiple points. Secondly, the physical structure and learning method was studied for the sub-elements in the fusion network. Thirdly, the spatio-temporal prediction algorithm was proposed based on the network for the blind area monitoring problem. Finally, the experiment was conducted with the practical monitoring data in an industrial park in Hebei Province, China. The results show that the solution is feasible for the blind area analysis in the view of spatial and temporal dimensions. |
format | Online Article Text |
id | pubmed-6843783 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68437832019-11-25 Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network Bai, Yu-ting Wang, Xiao-yi Sun, Qian Jin, Xue-bo Wang, Xiao-kai Su, Ting-li Kong, Jian-lei Int J Environ Res Public Health Article The monitoring-blind area exists in the industrial park because of private interest and limited administrative power. As the atmospheric quality in the blind area impacts the environment management seriously, the prediction and inference of the blind area is explored in this paper. Firstly, the fusion network framework was designed for the solution of “Circumjacent Monitoring-Blind Area Inference”. In the fusion network, the nonlinear autoregressive network was set up for the time series prediction of circumjacent points, and the full connection layer was built for the nonlinear relation fitting of multiple points. Secondly, the physical structure and learning method was studied for the sub-elements in the fusion network. Thirdly, the spatio-temporal prediction algorithm was proposed based on the network for the blind area monitoring problem. Finally, the experiment was conducted with the practical monitoring data in an industrial park in Hebei Province, China. The results show that the solution is feasible for the blind area analysis in the view of spatial and temporal dimensions. MDPI 2019-10-09 2019-10 /pmc/articles/PMC6843783/ /pubmed/31600885 http://dx.doi.org/10.3390/ijerph16203788 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bai, Yu-ting Wang, Xiao-yi Sun, Qian Jin, Xue-bo Wang, Xiao-kai Su, Ting-li Kong, Jian-lei Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title | Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title_full | Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title_fullStr | Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title_full_unstemmed | Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title_short | Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network |
title_sort | spatio-temporal prediction for the monitoring-blind area of industrial atmosphere based on the fusion network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843783/ https://www.ncbi.nlm.nih.gov/pubmed/31600885 http://dx.doi.org/10.3390/ijerph16203788 |
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