Emerging trends in machine learning to predict crop yield and study its influential factors: A survey
Agriculture is one of the most crucial field contributing to the development of any nation. It
not only affects the economy of nation but also has impact on the world food grain statistics …
not only affects the economy of nation but also has impact on the world food grain statistics …
Application of an artificial neural network to optimise energy inputs: An energy-and cost-saving strategy for commercial poultry farms
E Elahi, Z Zhang, Z Khalid, H Xu - Energy, 2022 - Elsevier
The current study estimates target values of energy inputs along with an assessment of
energy-and cost-saving strategies for poultry farms. In 2019, cross-sectional data were …
energy-and cost-saving strategies for poultry farms. In 2019, cross-sectional data were …
Potential for optimization of energy consumption and costs in saffron production in central Iran through data envelopment analysis and multi‐objective genetic …
E Saeidi, AL Dehkordi… - … Progress & Sustainable …, 2022 - Wiley Online Library
Technical management of agricultural units plays an important role in increasing the yield,
energy efficiency, and decreasing the production costs. Based on that, the present study …
energy efficiency, and decreasing the production costs. Based on that, the present study …
[HTML][HTML] Predicting crop yields using a new robust Bayesian averaging model based on multiple hybrid ANFIS and MLP models
Predicting crop yield is an important issue for farmers. Food security is important for decision-
makers. The agriculture industry can more accurately supply human demand for food if the …
makers. The agriculture industry can more accurately supply human demand for food if the …
Selection of independent variables for crop yield prediction using artificial neural network models with remote sensing data
P Hara, M Piekutowska, G Niedbała - Land, 2021 - mdpi.com
Knowing the expected crop yield in the current growing season provides valuable
information for farmers, policy makers, and food processing plants. One of the main benefits …
information for farmers, policy makers, and food processing plants. One of the main benefits …
[HTML][HTML] ANFIS and ANNs model for prediction of moisture diffusivity and specific energy consumption potato, garlic and cantaloupe drying under convective hot air …
The main purpose of this study was to develop and apply an adaptive neuro-fuzzy inference
system (ANFIS) and Artificial Neural Networks (ANNs) model for predicting the drying …
system (ANFIS) and Artificial Neural Networks (ANNs) model for predicting the drying …
Estimation of realistic renewable and non-renewable energy use targets for livestock production systems utilising an artificial neural network method: A step towards …
E Elahi, C Weijun, SK Jha, H Zhang - Energy, 2019 - Elsevier
This study estimated energy use flow of buffalo farms, energy use indices, production
efficiency, energy use targets, impact of energy inputs on energy output, and sensitivity …
efficiency, energy use targets, impact of energy inputs on energy output, and sensitivity …
Assessment of energy consumption and modeling of output energy for wheat production by neural network (MLP and RBF) and Gaussian process regression (GPR) …
The objective of this study was to predict the irrigated and rainfed wheat output energy with
three soft computing models include Artificial Neural Network (MLP and RBF models) and …
three soft computing models include Artificial Neural Network (MLP and RBF models) and …
The effects of winter cover crops on maize yield and crop performance in semiarid conditions—Artificial neural network approach
Maize is the most widespread and, along with wheat, the most important staple crop in the
Republic of Serbia, which is of great significance for ensuring national food security. With the …
Republic of Serbia, which is of great significance for ensuring national food security. With the …
Estimation of the energy production of a parabolic trough solar thermal power plant using analytical and artificial neural networks models
The accurate estimation of a concentrated solar power plant production is an important issue
because of the fluctuations in meteorological parameters like solar radiation, ambient …
because of the fluctuations in meteorological parameters like solar radiation, ambient …