Fault prediction based on leakage current in contaminated insulators using enhanced time series forecasting models
To improve the monitoring of the electrical power grid, it is necessary to evaluate the
influence of contamination in relation to leakage current and its progression to a disruptive …
influence of contamination in relation to leakage current and its progression to a disruptive …
Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions
Point-of-Care-Testing (PoCT) has emerged as an essential component of modern
healthcare, providing rapid, low-cost, and simple diagnostic options. The integration of …
healthcare, providing rapid, low-cost, and simple diagnostic options. The integration of …
The acceptable R-square in empirical modelling for social science research
PK Ozili - Social research methodology and publishing results: A …, 2023 - igi-global.com
This chapter examines the acceptable R-square in social science empirical modelling with
particular focus on why a low R-square model is acceptable in empirical social science …
particular focus on why a low R-square model is acceptable in empirical social science …
[HTML][HTML] Robust machine learning algorithms for predicting coastal water quality index
Coastal water quality assessment is an essential task to keep “good water quality” status for
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …
A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model
X Gu, KW See, P Li, K Shan, Y Wang, L Zhao, KC Lim… - Energy, 2023 - Elsevier
Abstract State-of-health (SOH) estimation of lithium-ion batteries is crucial for ensuring the
reliability and safety of battery operation while keeping maintenance and service costs down …
reliability and safety of battery operation while keeping maintenance and service costs down …
[HTML][HTML] Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management
Background: In the current global market, supply chains are increasingly complex,
necessitating agile and sustainable management strategies. Traditional analytical methods …
necessitating agile and sustainable management strategies. Traditional analytical methods …
Substantiation of drilling parameters for undermined drainage boreholes for increasing methane production from unconventional coal-gas collectors
BV Malozyomov, VI Golik, V Brigida, VV Kukartsev… - Energies, 2023 - mdpi.com
Decarbonization of the mining industry on the basis of closing the energy generation, on the
basis of cogeneration of coal mine methane, and on the internal consumption of the mine is …
basis of cogeneration of coal mine methane, and on the internal consumption of the mine is …
[HTML][HTML] Marine waters assessment using improved water quality model incorporating machine learning approaches
In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …
It depends on a number of factors, and one of the most important is the quality of the water …
Machine learning reveals climate forcing from aerosols is dominated by increased cloud cover
Aerosol–cloud interactions have a potentially large impact on climate but are poorly
quantified and thus contribute a substantial and long-standing uncertainty in climate …
quantified and thus contribute a substantial and long-standing uncertainty in climate …
[HTML][HTML] Machine learning models for the prediction of total yield and specific surface area of biochar derived from agricultural biomass by pyrolysis
Organic biomass pyrolysis to produce biochar is a viable approach to sustainably convert
agricultural residues. The yield and SSA of biochar are contingent upon the biomass type …
agricultural residues. The yield and SSA of biochar are contingent upon the biomass type …