A comprehensive survey on recent metaheuristics for feature selection
Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …
preprocessing due to the ever-increasing sizes in actual data. There have been many …
[HTML][HTML] Recent advances in electrochemical biosensors: Applications, challenges, and future scope
A Singh, A Sharma, A Ahmed, AK Sundramoorthy… - Biosensors, 2021 - mdpi.com
The electrochemical biosensors are a class of biosensors which convert biological
information such as analyte concentration that is a biological recognition element …
information such as analyte concentration that is a biological recognition element …
Graphmae: Self-supervised masked graph autoencoders
Self-supervised learning (SSL) has been extensively explored in recent years. Particularly,
generative SSL has seen emerging success in natural language processing and other …
generative SSL has seen emerging success in natural language processing and other …
Distance-based support vector machine to predict DNA N6-methyladenine modification
Background: DNA N6-methyladenine plays an important role in the restriction-modification
system to isolate invasion from adventive DNA. The shortcomings of the high time …
system to isolate invasion from adventive DNA. The shortcomings of the high time …
Rethinking graph neural networks for anomaly detection
Abstract Graph Neural Networks (GNNs) are widely applied for graph anomaly detection. As
one of the key components for GNN design is to select a tailored spectral filter, we take the …
one of the key components for GNN design is to select a tailored spectral filter, we take the …
[HTML][HTML] Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction
D Markovics, MJ Mayer - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The increase of the worldwide installed photovoltaic (PV) capacity and the intermittent
nature of the solar resource highlights the importance of power forecasting for the grid …
nature of the solar resource highlights the importance of power forecasting for the grid …
Artificial intelligence in E-Commerce: a bibliometric study and literature review
This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …
guidelines on how information systems (IS) research could contribute to this research …
Power of data in quantum machine learning
The use of quantum computing for machine learning is among the most exciting prospective
applications of quantum technologies. However, machine learning tasks where data is …
applications of quantum technologies. However, machine learning tasks where data is …
Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets
In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR)
dependence leads to clinically aggressive tumors with few therapeutic options. We used …
dependence leads to clinically aggressive tumors with few therapeutic options. We used …
Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …