Well production forecasting based on ARIMA-LSTM model considering manual operations
Accurate and efficient prediction of well production is essential for extending a well's life
cycle and improving reservoir recovery. Traditional models require expensive computational …
cycle and improving reservoir recovery. Traditional models require expensive computational …
Time series analysis of climate variables using seasonal ARIMA approach
The dynamic structure of climate is governed by changes in precipitation and temperature
and can be studied by time series analysis of these factors. This paper describes …
and can be studied by time series analysis of these factors. This paper describes …
Sustainable futures in agricultural heritage: Geospatial exploration and predicting groundwater-level variations in Barind tract of Bangladesh
HM Rasel, MA Al Mamun, A Hasnat, S Alam… - Science of The Total …, 2023 - Elsevier
Groundwater resources are one of the essential aspects of achieving self-sufficiency in a
country's agricultural production, poverty alleviation, and socioeconomic development …
country's agricultural production, poverty alleviation, and socioeconomic development …
[HTML][HTML] Using recurrent neural networks for localized weather prediction with combined use of public airport data and on-site measurements
Weather data is a crucial input for myriad applications in the built environment, including
building energy modeling and daylight analysis. Building science practitioners and …
building energy modeling and daylight analysis. Building science practitioners and …
Time series analysis of groundwater levels and projection of future trend
A study was under taken for identifying the trends in pre and post-monsoon groundwater
levels using Mann-Kendall test and Sen's slope estimator, and for time series modelling of …
levels using Mann-Kendall test and Sen's slope estimator, and for time series modelling of …
[PDF][PDF] Integration of machine learning (ML) and finite element analysis (FEA) for predicting the failure modes of a small horizontal composite blade
This article aims to integrate machine learning (ML) methodologies and Finite Element
Analysis (FEA) to analyze wind turbine blades made of composite material. The methods for …
Analysis (FEA) to analyze wind turbine blades made of composite material. The methods for …
An ensemble n-sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA
We analyze an ensemble of n-sub-epidemic modeling for forecasting the trajectory of
epidemics and pandemics. These ensemble modeling approaches, and models that …
epidemics and pandemics. These ensemble modeling approaches, and models that …
Trend analysis and ARIMA modelling of recent groundwater levels in the White Volta River basin of Ghana
Groundwater based irrigation in sub-Saharan African is believed to hold the key for
economic growth and poverty reduction. However, the associated consequences of the …
economic growth and poverty reduction. However, the associated consequences of the …
[HTML][HTML] SubEpiPredict: A tutorial-based primer and toolbox for fitting and forecasting growth trajectories using the ensemble n-sub-epidemic modeling framework
An ensemble n-sub-epidemic modeling framework that integrates sub-epidemics to capture
complex temporal dynamics has demonstrated powerful forecasting capability in previous …
complex temporal dynamics has demonstrated powerful forecasting capability in previous …
SpatialWavePredict: a tutorial-based primer and toolbox for forecasting growth trajectories using the ensemble spatial wave sub-epidemic modeling framework
Background Dynamical mathematical models defined by a system of differential equations
are typically not easily accessible to non-experts. However, forecasts based on these types …
are typically not easily accessible to non-experts. However, forecasts based on these types …