Air Quality Forecasting in Madrid Using Long Short-Term Memory Networks

被引：24

作者：

Pardo, Esteban ^{[1
]}

Malpica, Norberto ^{[1
]}

机构：

[1] Univ Rey Juan Carlos, Madrid, Spain

来源：

BIOMEDICAL APPLICATIONS BASED ON NATURAL AND ARTIFICIAL COMPUTING, PT II | 2017年 / 10338卷

关键词：

Air quality forecasting; Long short-term memory;

D O I：

10.1007/978-3-319-59773-7_24

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

European and Spanish legislation set hourly limits for Nitrogen Dioxide, NO2, that are enforced with traffic restrictions. In this context it is important to warn the citizens in advance, which can only be done if the NO2 levels are forecasted. In this paper we propose a deep learning based air quality forecasting system that uses air quality and meteorological data to produce NO2 forecasts up to 24 h with a root mean squared error, RMSE, of 10.54 mu g/m(3). We also compare our results with the model based system CALIOPE.

引用

页码：232 / 239

页数：8

共 50 条

[1] Long Short-Term Memory Approach for Short-Term Air Quality Forecasting in the Bay of Algeciras (Spain)
Rodriguez-Garcia, Maria Inmaculada
Carrasco-Garcia, Maria Gema
Gonzalez-Enrique, Javier
Ruiz-Aguilar, Juan Jesus
Turias, Ignacio J.
[J]. SUSTAINABILITY, 2023, 15 (06)
[2] Long Short Term Memory Networks for Short-Term Electric Load Forecasting
Narayan, Apurva
Hipel, Keith W.
[J]. 2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2017, : 2573 - 2578
[3] Short-Term Load Forecasting using A Long Short-Term Memory Network
Liu, Chang
Jin, Zhijian
Gu, Jie
Qiu, Caiming
[J]. 2017 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE), 2017,
[4] Forecasting container throughput with long short-term memory networks
Shankar, Sonali
Ilavarasan, P. Vigneswara
Punia, Sushil
Singh, Surya Prakash
[J]. INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2020, 120 (03) : 425 - 441
[5] Short-term and Long-term Air Quality Forecasting Technique Using Stacked LSTM
Sani, Shaon Hossain
Shopon, Md
Khan, Mashrur Hossain
Hasan, Moenul
Mridha, M. F.
[J]. 2020 6TH INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION PROCESSING, ICCIP 2020, 2020, : 165 - 171
[6] Short-term traffic travel time forecasting using ensemble approach based on long short-term memory networks
Jia, Xingli
Zhou, Wuxiao
Yang, Hongzhi
Li, Shuangqing
Chen, Xingpeng
[J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2023, 17 (06) : 1262 - 1273
[7] Industrial Financial Forecasting using Long Short-Term Memory Recurrent Neural Networks
Ali, Muhammad Mohsin
Babar, Muhammad Imran
Hamza, Muhammad
Jehanzeb, Muhammad
Habib, Saad
Khan, Muhammad Sajid
[J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (04) : 88 - 99
[8] Forecasting Methane Data Using Multivariate Long Short-Term Memory Neural Networks
Luo, Ran
Wang, Jingyi
Gates, Ian
[J]. ENVIRONMENTAL MODELING & ASSESSMENT, 2024, 29 (03) : 441 - 454
[9] Forecasting Arctic Sea Ice Concentration using Long Short-term Memory Networks
Phutthaphaiboon, Thunchanok
Siripongwutikorn, Peerapon
Pusawiro, Priyakorn
[J]. PROCEEDINGS OF 2023 8TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING TECHNOLOGIES, ICMLT 2023, 2023, : 121 - 126
[10] Photovoltaic power forecasting with a long short-term memory autoencoder networks
Mohammed Sabri
Mohammed El Hassouni
[J]. Soft Computing, 2023, 27 : 10533 - 10553

← 1 2 3 4 5 →