Machine learning in agriculture: A review
Machine learning has emerged with big data technologies and high-performance computing
to create new opportunities for data intensive science in the multi-disciplinary agri …
to create new opportunities for data intensive science in the multi-disciplinary agri …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
Crop prediction model using machine learning algorithms
Machine learning applications are having a great impact on the global economy by
transforming the data processing method and decision making. Agriculture is one of the …
transforming the data processing method and decision making. Agriculture is one of the …
Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm
B Mohammadi, S Mehdizadeh - Agricultural Water Management, 2020 - Elsevier
In achieving water resource management goals such as irrigation scheduling, an accurate
estimate of reference evapotranspiration (ET 0) is critical. Support vector regression (SVR) …
estimate of reference evapotranspiration (ET 0) is critical. Support vector regression (SVR) …
Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
F Granata - Agricultural Water Management, 2019 - Elsevier
The constant need to increase agricultural production, together with the more and more
frequent drought events in many areas of the world, requires a more careful assessment of …
frequent drought events in many areas of the world, requires a more careful assessment of …
Estimation of reference evapotranspiration in Brazil with limited meteorological data using ANN and SVM–A new approach
LB Ferreira, FF da Cunha, RA de Oliveira… - Journal of …, 2019 - Elsevier
Reference evapotranspiration (ET o) is a variable of great importance for several purposes,
such as hydrological studies and irrigation scheduling. The FAO-56 Penman-Monteith (FAO …
such as hydrological studies and irrigation scheduling. The FAO-56 Penman-Monteith (FAO …
Reference evapotranspiration estimation and modeling of the Punjab Northern India using deep learning
Over the last decade, the combination of both big data and machine learning research
area's receiving considerable attention and expedite the prospect of the agricultural industry …
area's receiving considerable attention and expedite the prospect of the agricultural industry …
LoRa based intelligent soil and weather condition monitoring with internet of things for precision agriculture in smart cities
Urbanization is expected to hold about 50% of the world population by 2050 and there will
be stress on available resources including food and freshwater. Further, inefficient utilization …
be stress on available resources including food and freshwater. Further, inefficient utilization …
Modeling reference evapotranspiration using extreme learning machine and generalized regression neural network only with temperature data
Accurate estimation of reference evapotranspiration (ET 0) is essential to agricultural water
management. The present study developed two artificial intelligence models for daily ET 0 …
management. The present study developed two artificial intelligence models for daily ET 0 …