[HTML][HTML] Deep learning based computer vision approaches for smart agricultural applications
The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
Collision cross section prediction based on machine learning
X Li, H Wang, M Jiang, M Ding, X Xu, B Xu, Y Zou, Y Yu… - Molecules, 2023 - mdpi.com
Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an
additional dimension of separation to support the enhanced separation and characterization …
additional dimension of separation to support the enhanced separation and characterization …
Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data
This study investigates the feasibility of a relevance vector machine tuned with improved
Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using …
Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using …
Modeling potential evapotranspiration by improved machine learning methods using limited climatic data
Modeling potential evapotranspiration (ET0) is an important issue for water resources
planning and management projects involving droughts and flood hazards …
planning and management projects involving droughts and flood hazards …
A survey towards decision support system on smart irrigation scheduling using machine learning approaches
From last decade, Big data analytics and machine learning is a hotspot research area in the
domain of agriculture. Agriculture analytics is a data intensive multidisciplinary problem. Big …
domain of agriculture. Agriculture analytics is a data intensive multidisciplinary problem. Big …
A comparison of machine learning models for predicting rainfall in urban metropolitan cities
Current research studies offer an investigation of machine learning methods used for
forecasting rainfall in urban metropolitan cities. Time series data, distinguished by their …
forecasting rainfall in urban metropolitan cities. Time series data, distinguished by their …
Hybridization of deep learning, nonlinear system identification and ensemble tree intelligence algorithms for pan evaporation estimation
A reliable pan evaporation (E pan) estimation over a daily scale is vital for sustainable water
and agriculture management, especially for designing water use allocations, irrigation …
and agriculture management, especially for designing water use allocations, irrigation …
A comprehensive review of artificial intelligence-based methods for predicting pan evaporation rate
This comprehensive study reviews the latest and most popular artificial intelligence (AI)
techniques utilised for estimating pan evaporation (Ep), an essential parameter for water …
techniques utilised for estimating pan evaporation (Ep), an essential parameter for water …
Short-and mid-term forecasts of actual evapotranspiration with deep learning
Evapotranspiration is a key component of the hydrologic cycle. Accurate short-, medium-,
and long-term forecasts of actual evapotranspiration (ET a) are crucial not only for …
and long-term forecasts of actual evapotranspiration (ET a) are crucial not only for …
[HTML][HTML] Assessing the impacts of temperature extremes on agriculture yield and projecting future extremes using machine learning and deep learning approaches …
Climate change, particularly extreme weather events, has significantly affected various
sectors, including agriculture, human health, water resources, sea levels, and ecosystems. It …
sectors, including agriculture, human health, water resources, sea levels, and ecosystems. It …