[1]
|
Estimation and analysis of missing temperature data in high altitude and snow-dominated regions using various machine learning methods
Environmental Monitoring and Assessment,
2023
DOI:10.1007/s10661-023-11143-7
|
|
|
[2]
|
Estimation and analysis of missing temperature data in high altitude and snow-dominated regions using various machine learning methods
Environmental Monitoring and Assessment,
2023
DOI:10.1007/s10661-023-11143-7
|
|
|
[3]
|
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Geoscientific Model Development,
2022
DOI:10.5194/gmd-15-9015-2022
|
|
|
[4]
|
Performance evaluation of a recurrent deep neural network optimized by swarm intelligent techniques to model particulate matter
Journal of the Air & Waste Management Association,
2022
DOI:10.1080/10962247.2022.2095057
|
|
|
[5]
|
A decomposition-ensemble broad learning system for AQI forecasting
Neural Computing and Applications,
2022
DOI:10.1007/s00521-022-07448-2
|
|
|
[6]
|
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Geoscientific Model Development,
2022
DOI:10.5194/gmd-15-9015-2022
|
|
|
[7]
|
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Geoscientific Model Development,
2022
DOI:10.5194/gmd-15-9015-2022
|
|
|
[8]
|
The Environmental Story During the COVID-19 Lockdown: How Human Activities Affect PM2.5 Concentration in China?
IEEE Geoscience and Remote Sensing Letters,
2022
DOI:10.1109/LGRS.2020.3040435
|
|
|
[9]
|
Sustainable Policies and Practices in Energy, Environment and Health Research
World Sustainability Series,
2022
DOI:10.1007/978-3-030-86304-3_37
|
|
|
[10]
|
PM10 Parametresinin Makine Öğrenmesi Algoritmalari ile Mekânsal Analizi, Kayseri İli Örneği
Deu Muhendislik Fakultesi Fen ve Muhendislik,
2022
DOI:10.21205/deufmd.2022247008
|
|
|
[11]
|
The Role of GARCH Effect on the Prediction of Air Pollution
Sustainability,
2022
DOI:10.3390/su14084459
|
|
|
[12]
|
Pattern Recognition
Lecture Notes in Computer Science,
2022
DOI:10.1007/978-3-031-07750-0_12
|
|
|
[13]
|
Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives
Fundamental Research,
2021
DOI:10.1016/j.fmre.2021.04.007
|
|
|
[14]
|
Neural Computing for Advanced Applications
Communications in Computer and Information Science,
2021
DOI:10.1007/978-981-16-5188-5_54
|
|
|
[15]
|
Application of Photo Texture Analysis and Weather Data in Assessment of Air Quality in Terms of Airborne PM10 and PM2.5 Particulate Matter
Sensors,
2021
DOI:10.3390/s21165483
|
|
|
[16]
|
Airborne Particulate Matter Modeling: A Comparison of Three Methods Using a Topology Performance Approach
Applied Sciences,
2021
DOI:10.3390/app12010256
|
|
|
[17]
|
Intelligent modeling strategies for forecasting air quality time series: A review
Applied Soft Computing,
2021
DOI:10.1016/j.asoc.2020.106957
|
|
|
[18]
|
Investigation of PM10 prediction utilizing data mining techniques: Analyze by topic
WIREs Data Mining and Knowledge Discovery,
2021
DOI:10.1002/widm.1423
|
|
|
[19]
|
Source number estimation based on a novel multi-view meta-hierarchical classification framework
Measurement Science and Technology,
2020
DOI:10.1088/1361-6501/ab6a46
|
|
|
[20]
|
A Machine Learning Approach to Predict Air Quality in California
Complexity,
2020
DOI:10.1155/2020/8049504
|
|
|
[21]
|
Chemometrics for environmental monitoring: a review
Analytical Methods,
2020
DOI:10.1039/D0AY01389G
|
|
|
[22]
|
Predictive analytics of PM10 concentration levels using detailed traffic data
Transportation Research Part D: Transport and Environment,
2019
DOI:10.1016/j.trd.2018.11.015
|
|
|
[23]
|
Application of statistical techniques in environmental modelling
APPLIED PHYSICS OF CONDENSED MATTER (APCOM 2019),
2019
DOI:10.1063/1.5118082
|
|
|
[24]
|
Using geosocial search for urban air pollution monitoring
Pervasive and Mobile Computing,
2017
DOI:10.1016/j.pmcj.2016.07.001
|
|
|
[25]
|
A spatio-temporal prediction model based on support vector machine regression: Ambient Black Carbon in three New England States
Environmental Research,
2017
DOI:10.1016/j.envres.2017.08.039
|
|
|
[26]
|
Statistical Modeling Approaches for PM10 Prediction in Urban Areas; A Review of 21st-Century Studies
Atmosphere,
2016
DOI:10.3390/atmos7020015
|
|
|
[27]
|
Using wavelet–feedforward neural networks to improve air pollution forecasting in urban environments
Environmental Monitoring and Assessment,
2015
DOI:10.1007/s10661-015-4697-x
|
|
|
[28]
|
Enhancement of a Neuro-Fuzzy Models Using Ant Colony Optimization for the Prediction Level of CO Pollution
2014 13th Mexican International Conference on Artificial Intelligence,
2014
DOI:10.1109/MICAI.2014.28
|
|
|
[29]
|
Method to Improve Airborne Pollution Forecasting by Using Ant Colony Optimization and Neuro-Fuzzy Algorithms
International Journal of Intelligence Science,
2014
DOI:10.4236/ijis.2014.44010
|
|
|