Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach

M Vafaeipour, SH Zolfani, MHM Varzandeh… - Energy Conversion and …, 2014 - Elsevier
One of the promising ways to shift towards sustainable development has been the utilization
of solar energy worldwide. Based on its geographical specifications, Iran enjoys high solar …

Wavelet-multi resolution analysis based ANN architecture for fault detection and localization in DC microgrids

D Jayamaha, NWA Lidula, AD Rajapakse - IEEE Access, 2019 - ieeexplore.ieee.org
DC microgrids present an effective power system solution for increased integration of
renewable sources while providing clear benefits, such as high efficiency and simpler …

Prediction of Chlorophyll-a Concentrations in the Nakdong River Using Machine Learning Methods

Y Shin, T Kim, S Hong, S Lee, EJ Lee, SW Hong… - Water, 2020 - mdpi.com
Many studies have attempted to predict chlorophyll-a concentrations using multiple
regression models and validating them with a hold-out technique. In this study commonly …

[PDF][PDF] Time series data prediction using sliding window based RBF neural network

HS Hota, R Handa, AK Shrivas - International Journal of …, 2017 - academia.edu
Time series data are data which are taken in a particular time interval, and may vary
drastically during the period of observation and hence it becomes highly nonlinear. Stock …

Water quality prediction in the luan river based on 1-drcnn and bigru hybrid neural network model

J Yan, J Liu, Y Yu, H Xu - Water, 2021 - mdpi.com
The current global water environment has been seriously damaged. The prediction of water
quality parameters can provide effective reference materials for future water conditions and …

Energy generation forecasting: elevating performance with machine and deep learning

A Mystakidis, E Ntozi, K Afentoulis, P Koukaras… - Computing, 2023 - Springer
Abstract Distribution System Operators (DSOs) and Aggregators benefit from novel Energy
Generation Forecasting (EGF) approaches. Improved forecasting accuracy may make it …

[HTML][HTML] A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines

M Subramaniyan, A Skoogh, H Salomonsson… - Computers & Industrial …, 2018 - Elsevier
Smart manufacturing is reshaping the manufacturing industry by boosting the integration of
information and communication technologies and manufacturing process. As a result …

[HTML][HTML] A predictive maintenance model using long short-term memory neural networks and Bayesian inference

D Pagano - Decision Analytics Journal, 2023 - Elsevier
The fourth industrial revolution is a profound transformation utilizing emerging technologies
like smart automation, large-scale machine-to-machine communication, and the internet of …

Real-time prediction of rate of penetration by combining attention-based gated recurrent unit network and fully connected neural networks

C Zhang, X Song, Y Su, G Li - Journal of Petroleum Science and …, 2022 - Elsevier
Data-driven models are widely used to predict rate of penetration. However, there are still
challenges on real-time predictions considering influences of formation properties and bit …

Detecting spectre attacks using hardware performance counters

C Li, JL Gaudiot - IEEE Transactions on Computers, 2021 - ieeexplore.ieee.org
Spectre attacks can be catastrophic and widespread because they exploit common design
flaws caused by the speculative capabilities in modern processors to leak sensitive data …