Smart farming using artificial intelligence: A review
Smart farming with artificial intelligence provides an efficient solution to today's agricultural
sustainability challenges. Machine learning, Deep learning, and time series analysis are …
sustainability challenges. Machine learning, Deep learning, and time series analysis are …
Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review
Prognostics and health management (PHM) has emerged as a vital research discipline for
optimizing the maintenance of operating systems by detecting health degradation and …
optimizing the maintenance of operating systems by detecting health degradation and …
Forecasting of solar radiation using different machine learning approaches
V Demir, H Citakoglu - Neural Computing and Applications, 2023 - Springer
In this study, monthly solar radiation (SR) estimation was performed using five different
machine learning-based approaches. The models used are support vector machine …
machine learning-based approaches. The models used are support vector machine …
[HTML][HTML] A systematic review on machine learning and deep learning models for electronic information security in mobile networks
Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …
tremendous volume of data being generated. Most of our information is part of a widespread …
[HTML][HTML] Multi-swarm algorithm for extreme learning machine optimization
There are many machine learning approaches available and commonly used today,
however, the extreme learning machine is appraised as one of the fastest and, additionally …
however, the extreme learning machine is appraised as one of the fastest and, additionally …
Prediction of the standardized precipitation index based on the long short-term memory and empirical mode decomposition-extreme learning machine models: The …
Ö Coşkun, H Citakoglu - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
This research predicted the meteorological drought of Sakarya province in northwest Türkiye
using long short-term memory (LSTM). This deep learning algorithm has gained popularity …
using long short-term memory (LSTM). This deep learning algorithm has gained popularity …
Forecasting carbon price trends based on an interpretable light gradient boosting machine and Bayesian optimization
S Deng, J Su, Y Zhu, Y Yu, C Xiao - Expert Systems with Applications, 2024 - Elsevier
The future carbon price is crucial to relevant companies, investors, and carbon
policymakers, and the significance of carbon price prediction research is self-evident …
policymakers, and the significance of carbon price prediction research is self-evident …
TWC-EL: A multivariate prediction model by the fusion of three-way clustering and ensemble learning
X Wu, J Zhan, W Ding - Information Fusion, 2023 - Elsevier
Multivariate data analysis, as an important research topic in the field of machine learning,
focuses on how to utilize the intrinsic connection between feature variables and target …
focuses on how to utilize the intrinsic connection between feature variables and target …
Design and testing novel one-class classifier based on polynomial interpolation with application to networking security
P Dini, A Begni, S Ciavarella, E De Paoli… - IEEE …, 2022 - ieeexplore.ieee.org
This work exploits the concept of one-class classifier applied to the problem of anomaly
detection in communication networks. The article presents the design of an innovative …
detection in communication networks. The article presents the design of an innovative …
A review of recent advances and applications of machine learning in tribology
In tribology, a considerable number of computational and experimental approaches to
understand the interfacial characteristics of material surfaces in motion and tribological …
understand the interfacial characteristics of material surfaces in motion and tribological …