A spatial correlation prediction model of urban <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si5.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">PM</mml:mi></mml:mrow><mml:mrow><mml:mn>2.5</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> concentration based on deconvolution and LSTM-Reference-Cited by-同舟云学术

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A spatial correlation prediction model of urban PM2.5 concentration based on deconvolution and LSTM

Published:2023-08 Issue: Volume:544 Page:126280
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Bo,Liu Yuan,Yong RuiHan,Zou Guojian,Yang Ru,Pan Jianguo,Li Maozhen

Funder

Natural Science Foundation of Shanghai

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference54 articles.

1. Breast cancer risk in association with atmospheric pollution exposure: a meta-analysis of effect estimates followed by a health impact assessment;Gabet;Environmental Health Perspectives,2021

2. Health impacts of air pollution in china;Fengping;Frontiers of Environmental Science & Engineering,2021

3. Links between air pollution and covid-19 in england;Travaglio;Environmental Pollution,2021

4. Evaluation of anthropogenic air pollutant emission inventories for south america at national and city scale;Huneeus;Atmospheric Environment,2020

5. Assessing exposure to outdoor air pollution for epidemiological studies: Model-based and personal sampling strategies;Brokamp;Journal of Allergy and Clinical Immunology,2019

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1. Artificial neural network an innovative approach in air pollutant prediction for environmental applications: A review;Results in Engineering;2024-06

2. Incorporating the Third Law of Geography with Spatial Attention Module–Convolutional Neural Network–Transformer for Fine-Grained Non-Stationary Air Quality Predictive Learning;Mathematics;2024-05-08

3. Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction;Scientific Reports;2024-05-06

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