相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。A deep spatio-temporal learning network for continuous citywide air quality forecast based on dense monitoring data
Rong Guo et al.
JOURNAL OF CLEANER PRODUCTION (2023)
Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies
Michael Wood et al.
FORECASTING (2023)
Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques
Jean-Maxime Bertrand et al.
ATMOSPHERIC CHEMISTRY AND PHYSICS (2023)
Unprecedented fire activity above the Arctic Circle linked to rising temperatures
Adria Descals et al.
SCIENCE (2022)
Modeling PM2.5 and PM10 Using a Robust Simplified Linear Regression Machine Learning Algorithm
Joao Gregorio et al.
ATMOSPHERE (2022)
Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Ricardo Petri Silva et al.
SENSORS (2021)
Air quality assessment and pollution forecasting using artificial neural networks in Metropolitan Lima-Peru
Chardin Hoyos Cordova et al.
SCIENTIFIC REPORTS (2021)
A Novel Recursive Model Based on a Convolutional Long Short-Term Memory Neural Network for Air Pollution Prediction
Weilin Wang et al.
REMOTE SENSING (2021)
A Framework to Predict High-Resolution Spatiotemporal PM2.5Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China
Guangyuan Zhang et al.
REMOTE SENSING (2020)
Markov Chains Modelling of Particulate Matter (PM10) Air Contamination in the City of Ruse, Bulgaria
E. Veleva et al.
APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES (AMITANS 2020) (2020)
Hybrid algorithm for short-term forecasting of PM2.5 in China
Yong Cheng et al.
ATMOSPHERIC ENVIRONMENT (2019)
Prediction of Air Pollution Concentration Based on mRMR and Echo State Network
Xinghan Xu et al.
APPLIED SCIENCES-BASEL (2019)
Application of a Hybrid Model Based on Echo State Network and Improved Particle Swarm Optimization in PM2.5 Concentration Forecasting: A Case Study of Beijing, China
Xinghan Xu et al.
SUSTAINABILITY (2019)
Markov Chain Model Development for Forecasting Air Pollution Index of Miri, Sarawak
Nurul Nnadiah Zakaria et al.
SUSTAINABILITY (2019)
Multi-model Ensemble Forecast of PM2.5 Concentration Based on the Improved Wavelet Neural Networks
Tao Li et al.
JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY (2019)
Regional Air Quality Forecast Using a Machine Learning Method and the WRF Model over the Yangtze River Delta, East China
Mengwei Jia et al.
AEROSOL AND AIR QUALITY RESEARCH (2019)
Local Arctic Air Pollution: A Neglected but Serious Problem
J. Schmale et al.
EARTHS FUTURE (2018)
Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation
Xiang Li et al.
ENVIRONMENTAL POLLUTION (2017)
Recursive neural network model for analysis and forecast of PM10 and PM2.5
Fabio Biancofiore et al.
ATMOSPHERIC POLLUTION RESEARCH (2017)
Local Arctic air pollution: Sources and impacts
Kathy S. Law et al.
AMBIO (2017)
Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5
Shadi Ausati et al.
ATMOSPHERIC ENVIRONMENT (2016)
Deep learning architecture for air quality predictions
Xiang Li et al.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2016)
Combining DMSP/OLS Nighttime Light with Echo State Network for Prediction of Daily PM2.5 Average Concentrations in Shanghai, China
Zhao Xu et al.
ATMOSPHERE (2015)
A regional air quality forecasting system over Europe: the MACC-II daily ensemble production
V. Marecal et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2015)
Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering
M. A. Elangasinghe et al.
ATMOSPHERIC ENVIRONMENT (2014)
Real-time air quality forecasting, part I: History, techniques, and current status
Yang Zhang et al.
ATMOSPHERIC ENVIRONMENT (2012)
Monsoonal differences and probability distribution of PM10 concentration
Noor Faizah Fitri Md Yusof et al.
ENVIRONMENTAL MONITORING AND ASSESSMENT (2010)
Forecasting air pollutant indicator levels with geographic models 3 days in advance using neural networks
Atakan Kurt et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Application of PM10's Statistical Distribution to Air Quality Management-A Case Study in Central Greece
Dimitris K. Papanastasiou et al.
WATER AIR AND SOIL POLLUTION (2010)
A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of Temuco, Chile
Luis A. Diaz-Robles et al.
ATMOSPHERIC ENVIRONMENT (2008)
Progress in developing an ANN model for air pollution index forecast
DH Jiang et al.
ATMOSPHERIC ENVIRONMENT (2004)
The statistical characters of PM10 concentration in Taiwan area
HC Lu
ATMOSPHERIC ENVIRONMENT (2002)