UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Impact of the COVID-19 outbreak on air pollution levels in East Asia

The Science of the total environment, 2021-02, Vol.754, p.142226-142226, Article 142226

2021

Volltextzugriff (PDF)

A real-time hourly ozone prediction system using deep convolutional neural network

Neural computing & applications, 2020-07, Vol.32 (13), p.8783-8797

2020

Volltextzugriff (PDF)

A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance

Scientific reports, 2021-05, Vol.11 (1), p.10891-10891, Article 10891

2021

Volltextzugriff (PDF)

Efficient PM2.5 forecasting using geographical correlation based on integrated deep learning algorithms

Neural computing & applications, 2021-11, Vol.33 (22), p.15073-15089

2021

Volltextzugriff (PDF)

Real-time 7-day forecast of pollen counts using a deep convolutional neural network

Neural computing & applications, 2020-08, Vol.32 (15), p.11827-11836

2020

Volltextzugriff (PDF)

A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks

Neural computing & applications, 2020-06, Vol.32 (11), p.7563-7579

2020

Volltextzugriff (PDF)

Development of Deep Convolutional Neural Network Ensemble Models for 36-Month ENSO Forecasts

Asia-Pacific Journal of Atmospheric Sciences, 2023, 59(5), , pp.597-605

2023

Volltextzugriff (PDF)

Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States

Environmental pollution (1987), 2023-06, Vol.326, p.121508-121508, Article 121508

2023

Volltextzugriff (PDF)

Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance

Neural networks, 2020-01, Vol.121, p.396-408

2020

Volltextzugriff (PDF)

CMAQ-CNN: A new-generation of post-processing techniques for chemical transport models using deep neural networks

Atmospheric environment (1994), 2022-03, Vol.273, p.118961, Article 118961

2022

Volltextzugriff (PDF)

Bias correcting and extending the PM forecast by CMAQ up to 7 days using deep convolutional neural networks

Atmospheric environment (1994), 2021-05, Vol.253, p.118376, Article 118376

2021

Volltextzugriff (PDF)

A Deep Convolutional Neural Network Model for Improving WRF Simulations

IEEE transaction on neural networks and learning systems, 2023-02, Vol.34 (2), p.750-760

2023

Volltextzugriff (PDF)

A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach

Atmospheric environment (1994), 2022-03, Vol.272, p.118944-118944, Article 118944

2022

Volltextzugriff (PDF)

Deep Learning Estimation of Daily Ground‐Level NO2 Concentrations From Remote Sensing Data

Journal of geophysical research. Atmospheres, 2021-11, Vol.126 (21), p.n/a

2021

Volltextzugriff (PDF)

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter

Environmental pollution (1987), 2022-10, Vol.310, p.119863-119863, Article 119863

2022

Volltextzugriff (PDF)

Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data

Geophysical research letters, 2021-08, Vol.48 (15), p.n/a

2021

Volltextzugriff (PDF)

CNN-based model for the spatial imputation (CMSI version 1.0) of in-situ ozone and PM2.5 measurements

Atmospheric environment (1994), 2022-11, Vol.289, p.119348, Article 119348

2022

Volltextzugriff (PDF)

Deep learning solver for solving advection–diffusion equation in comparison to finite difference methods

Communications in nonlinear science & numerical simulation, 2022-12, Vol.115, p.106780, Article 106780

2022

Volltextzugriff (PDF)

A comprehensive study of the COVID-19 impact on PM 2.5 levels over the contiguous United States: A deep learning approach

Atmospheric environment (1994), 2022-03, Vol.272, p.118944

2022

Volltextzugriff (PDF)

A Coupled Deep Learning Model for Estimating Surface NO2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States

Journal of geophysical research. Atmospheres, 2023-01, Vol.128 (2), p.n/a

2023

Volltextzugriff (PDF)

Spatiotemporal estimation of TROPOMI NO2 column with depthwise partial convolutional neural network

Neural computing & applications, 2023-07, Vol.35 (21), p.15667-15678

2023

Volltextzugriff (PDF)

A Coupled Deep Learning Model for Estimating Surface NO 2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States

Journal of geophysical research. Atmospheres, 2023-01, Vol.128 (2)

2023

Volltextzugriff (PDF)

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from Climate Models

Artificial intelligence for the earth systems, 2024-07, Vol.3 (3)

2024

Volltextzugriff (PDF)

Deep Learning Estimation of Daily Ground‐Level NO 2 Concentrations From Remote Sensing Data

Journal of geophysical research. Atmospheres, 2021-11, Vol.126 (21)

2021

Volltextzugriff (PDF)

Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system

Geoscientific Model Development, 2020-12, Vol.13 (12), p.6237-6251

2020

Volltextzugriff (PDF)

1 – 25 von 28

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(24)
Mit Volltextzugriff
(25)

Publikationsform

Artikel
(28)

Sprache

Englisch
(28)

Erscheinungsjahr

n.n

Thema

Science & Technology
(21)
Deep Learning
(11)
Neural Networks
(10)
Physical Sciences
(10)
Artificial Neural Networks
(9)
Environmental Sciences
(9)
Air Quality
(8)
Life Sciences & Biomedicine
(8)
Machine Learning
(8)
Technology
(8)
Computer Science
(7)
Computer Science, Artificial Intelligence
(7)
Environmental Sciences & Ecology
(7)
Meteorology & Atmospheric Sciences
(7)
Air Pollution
(6)
Algorithms
(6)
Artificial Intelligence
(6)
Forecasting
(6)
Outdoor Air Quality
(6)
Ozone
(6)

15 weitere anzeigen...

Weniger anzeigen...

Menü

Weitere Dienste

Einstellungen

Impact of the COVID-19 outbreak on air pollution levels in East Asia

A real-time hourly ozone prediction system using deep convolutional neural network

A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance

Efficient PM2.5 forecasting using geographical correlation based on integrated deep learning algorithms

Real-time 7-day forecast of pollen counts using a deep convolutional neural network

A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks

Development of Deep Convolutional Neural Network Ensemble Models for 36-Month ENSO Forecasts

Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States

Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance

CMAQ-CNN: A new-generation of post-processing techniques for chemical transport models using deep neural networks

Bias correcting and extending the PM forecast by CMAQ up to 7 days using deep convolutional neural networks

A Deep Convolutional Neural Network Model for Improving WRF Simulations

A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach

Deep Learning Estimation of Daily Ground‐Level NO2 Concentrations From Remote Sensing Data

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter

Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data

CNN-based model for the spatial imputation (CMSI version 1.0) of in-situ ozone and PM2.5 measurements

Deep learning solver for solving advection–diffusion equation in comparison to finite difference methods

A comprehensive study of the COVID-19 impact on PM 2.5 levels over the contiguous United States: A deep learning approach

A Coupled Deep Learning Model for Estimating Surface NO2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States

Spatiotemporal estimation of TROPOMI NO2 column with depthwise partial convolutional neural network

A Coupled Deep Learning Model for Estimating Surface NO 2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from Climate Models

Deep Learning Estimation of Daily Ground‐Level NO 2 Concentrations From Remote Sensing Data

Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system

Suchergebnisse filtern