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[HTML][HTML] Artificial intelligence technologies for forecasting air pollution and human health: a narrative review
Air pollution is a major issue all over the world because of its impacts on the environment
and human beings. The present review discussed the sources and impacts of pollutants on …
and human beings. The present review discussed the sources and impacts of pollutants on …
A review of modern machine learning techniques in the prediction of remaining useful life of lithium-ion batteries
The intense increase in air pollution caused by vehicular emissions is one of the main
causes of changing weather patterns and deteriorating health conditions. Furthermore …
causes of changing weather patterns and deteriorating health conditions. Furthermore …
[HTML][HTML] Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques
Concrete is a widely used construction material, and cement is its main constituent.
Production and utilization of cement severely affect the environment due to the emission of …
Production and utilization of cement severely affect the environment due to the emission of …
Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing
Soil organic carbon (SOC) is a key variable to determine soil functioning, ecosystem
services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral …
services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral …
[HTML][HTML] An LSTM neural network for improving wheat yield estimates by integrating remote sensing data and meteorological data in the Guanzhong Plain, PR China
H Tian, P Wang, K Tansey, J Zhang, S Zhang… - Agricultural and Forest …, 2021 - Elsevier
Crop growth condition and production play an important role in food management and
economic development. Therefore, estimating yield accurately and timely is of vital …
economic development. Therefore, estimating yield accurately and timely is of vital …
A novel model to predict significant wave height based on long short-term memory network
S Fan, N **ao, S Dong - Ocean Engineering, 2020 - Elsevier
A long short-term memory (LSTM) network is proposed for the quick prediction of significant
wave height with higher accuracy than conventional neural network. The LSTM network is …
wave height with higher accuracy than conventional neural network. The LSTM network is …
Prediction of hourly air temperature based on CNN–LSTM
J Hou, Y Wang, J Zhou, Q Tian - Geomatics, Natural Hazards and …, 2022 - Taylor & Francis
The prediction accuracy of hourly air temperature is generally poor because of random
changes, long time series, and the nonlinear relationship between temperature and other …
changes, long time series, and the nonlinear relationship between temperature and other …
Prediction and reconstruction of ocean wave heights based on bathymetric data using LSTM neural networks
C Jörges, C Berkenbrink, B Stumpe - Ocean Engineering, 2021 - Elsevier
Since climate change impacts threaten the coastal regions of the North Sea, consistent sea
state time series are essential for building coastal protection or offshore structures. Vast …
state time series are essential for building coastal protection or offshore structures. Vast …
Artificial neural networks in drought prediction in the 21st century–A scientometric analysis
Droughts are the most spatially complex geohazard, which often lasts for years, thereby
severely impacting socio-economic sectors. One of the critical aspects of drought studies is …
severely impacting socio-economic sectors. One of the critical aspects of drought studies is …
An improved SPEI drought forecasting approach using the long short-term memory neural network
Droughts are slow-moving natural hazards that gradually spread over large areas and
capable of extending to continental scales, leading to severe socio-economic damage. A …
capable of extending to continental scales, leading to severe socio-economic damage. A …