Artificial intelligence in animal farming: A systematic literature review

J Bao, Q Xie - Journal of Cleaner Production, 2022 - Elsevier
Some scientific researches have been conducted recently based on Artificial Intelligence
(AI) to solve animal welfare and health related problems. However, no review study was …

Comprehensive review of deep reinforcement learning methods and applications in economics

A Mosavi, Y Faghan, P Ghamisi, P Duan, SF Ardabili… - Mathematics, 2020 - mdpi.com
The popularity of deep reinforcement learning (DRL) applications in economics has
increased exponentially. DRL, through a wide range of capabilities from reinforcement …

Covid-19 outbreak prediction with machine learning

SF Ardabili, A Mosavi, P Ghamisi, F Ferdinand… - Algorithms, 2020 - mdpi.com
Several outbreak prediction models for COVID-19 are being used by officials around the
world to make informed decisions and enforce relevant control measures. Among the …

When smart cities get smarter via machine learning: An in-depth literature review

SS Band, S Ardabili, M Sookhak… - IEEE …, 2022 - ieeexplore.ieee.org
The manuscript represents a comeprehensive and systematic literature review on the
machine learning methods in the emerging applications of the smart cities. Application …

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 …

[HTML][HTML] Machine learning techniques for sequence-based prediction of viral–host interactions between SARS-CoV-2 and human proteins

L Dey, S Chakraborty, A Mukhopadhyay - Biomedical journal, 2020 - Elsevier
Abstract Background COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-
CoV-2 virus, has been declared as a pandemic by the World Health Organization on March …

A comparative study of neural networks and ANFIS for forecasting attendance rate of soccer games

M Şahin, R Erol - Mathematical and computational applications, 2017 - mdpi.com
The main purpose of this study was to develop and apply a neural network (NN) approach
and an adaptive neuro-fuzzy inference system (ANFIS) model for forecasting the attendance …

Artificial neural networks and adaptive neuro-fuzzy inference system in energy modeling of agricultural products

A Nabavi-Pelesaraei, S Rafiee… - Predictive modelling for …, 2021 - Elsevier
The expected yield of agricultural production is a significant factor in energy management,
because it can help us in an operation like detecting and diagnosing faults, conducting …

Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) …

YJ Wong, SK Arumugasamy, CH Chung… - Environmental …, 2020 - Springer
Presence of copper within water bodies deteriorates human health and degrades natural
environment. This heavy metal in water is treated using a promising biochar derived from …

Comparative analysis of ANN and SVM models combined with wavelet preprocess for groundwater depth prediction

T Zhou, F Wang, Z Yang - Water, 2017 - mdpi.com
Reliable prediction of groundwater depth fluctuations has been an important component in
sustainable water resources management. In this study, a data-driven prediction model …