Machine learning applications for precision agriculture: A comprehensive review
Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …
population, frequent changes in climatic conditions and limited resources, it becomes a …
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 …
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 …
Prediction of photovoltaic power output based on similar day analysis, genetic algorithm and extreme learning machine
Recently, many machine learning techniques have been successfully employed in
photovoltaic (PV) power output prediction because of their strong non-linear regression …
photovoltaic (PV) power output prediction because of their strong non-linear regression …
[PDF][PDF] Application of Extreme Learning Machine (ELM) and Genetic Programming (GP) to design steel-concrete composite floor systems at elevated temperatures
This study is aimed to predict the behaviour of channel shear connectors in composite floor
systems at different temperatures. For this purpose, a soft computing approach is adopted …
systems at different temperatures. For this purpose, a soft computing approach is adopted …
Forecasting corn yield with machine learning ensembles
The emergence of new technologies to synthesize and analyze big data with high-
performance computing has increased our capacity to more accurately predict crop yields …
performance computing has increased our capacity to more accurately predict crop yields …
Application of extreme learning machine for short term output power forecasting of three grid-connected PV systems
The power output (PO) of a photovoltaic (PV) system is highly variable because of its
dependence on solar irradiance and other meteorological factors. Hence, accurate PO …
dependence on solar irradiance and other meteorological factors. Hence, accurate PO …
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Monthly stream-flow forecasting can yield important information for hydrological applications
including sustainable design of rural and urban water management systems, optimization of …
including sustainable design of rural and urban water management systems, optimization of …
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 …