Integrating digital technologies in agriculture for climate change adaptation and mitigation: State of the art and future perspectives
Agriculture faces a major challenge in meeting the world's growing demand for food in a
sustainable manner in the face of increasing environmental pressures, in particular the …
sustainable manner in the face of increasing environmental pressures, in particular the …
Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models
Accurate measurement or estimation of plant transpiration (T) is of great significance for
understanding crop water use, predicting crop yield and designing irrigation schedule in …
understanding crop water use, predicting crop yield and designing irrigation schedule in …
A new methodology for reference evapotranspiration prediction and uncertainty analysis under climate change conditions based on machine learning, multi criteria …
In the present study, a new methodology for reference evapotranspiration (ETo) prediction
and uncertainty analysis under climate change and COVID-19 post-pandemic recovery …
and uncertainty analysis under climate change and COVID-19 post-pandemic recovery …
Review of artificial intelligence and internet of things technologies in land and water management research during 1991–2021: A bibliometric analysis
The challenges of urbanization, land degradation, water scarcity, and climate change are
threatening agricultural systems and food security. Therefore, it is essential to manage land …
threatening agricultural systems and food security. Therefore, it is essential to manage land …
Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index
In recent decades, various conventional techniques have been formulated around the world
to evaluate the overall water quality (WQ) at particular locations. In the present study, back …
to evaluate the overall water quality (WQ) at particular locations. In the present study, back …
Water quality prediction using machine learning models based on grid search method
Water quality is very dominant for humans, animals, plants, industries, and the environment.
In the last decades, the quality of water has been impacted by contamination and pollution …
In the last decades, the quality of water has been impacted by contamination and pollution …
Potential of RT, Bagging and RS ensemble learning algorithms for reference evapotranspiration prediction using climatic data-limited humid region in Bangladesh
Ensemble learning (EL), an alternative approach in the machine-learning field, offers an
accurate reference evapotranspiration (ETo) prediction, which is of paramount significance …
accurate reference evapotranspiration (ETo) prediction, which is of paramount significance …
Map** maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices
Rapid and accurate acquisition of crop coefficient (K c) values is essential for estimating field
crop evapotranspiration (ET). The lack of rapid access to the high-resolution spatial and …
crop evapotranspiration (ET). The lack of rapid access to the high-resolution spatial and …
A reinforced random forest model for enhanced crop yield prediction by integrating agrarian parameters
D Elavarasan, PMDR Vincent - Journal of Ambient Intelligence and …, 2021 - Springer
The development in technology and science has contributed to a vast volume of data from
various agrarian fields to be aggregated in the public domain. Predicting the crop yield …
various agrarian fields to be aggregated in the public domain. Predicting the crop yield …
An intelligent framework for prediction and forecasting of dissolved oxygen level and biofloc amount in a shrimp culture system using machine learning techniques
The present study approaches towards the feasibility of prediction and forecasting of
dissolved oxygen (DO) and biofloc amount using the state of art machine learning …
dissolved oxygen (DO) and biofloc amount using the state of art machine learning …