Results 31 to 40 of about 1,295,192 (344)
Large Margin and Minimal Reduced Enclosing Ball Learning Machine [PDF]
Journal of Software, 2012 Jianwen Tao, Shitong Wang
openalex +2 more sources
Pharmaceuticals, 2023 Predicting compound potency is a major task in computational medicinal chemistry, for which machine learning is often applied. This study systematically predicted compound potency values for 367 target-based compound activity classes from medicinal ...
Tiago Janela, Jürgen Bajorath
doaj +1 more source
IEEE Access, 2020 This article presents a machine learning approach to predict the long-term voltage stability margin as represented by the Loadability Margin (LM). LM is an intuitive and easily understandable indicator of voltage stability.
Kalana Dulanjith Dharmapala +3 more
doaj +1 more source
Machine learning for accurate estimation of fetal gestational age based on ultrasound images
npj Digital Medicine, 2023 Accurate estimation of gestational age is an essential component of good obstetric care and informs clinical decision-making throughout pregnancy. As the date of the last menstrual period is often unknown or uncertain, ultrasound measurement of fetal ...
L. H. Lee +21 more
semanticscholar +1 more source
Machine learning‑based prediction of survival prognosis in esophageal squamous cell carcinoma
Scientific Reports, 2023 The current prognostic tools for esophageal squamous cell carcinoma (ESCC) lack the necessary accuracy to facilitate individualized patient management strategies.
Kaijiong Zhang +7 more
semanticscholar +1 more source
IEEE Access, 2021 This paper proposes a computationally efficient method based on deep neural network and a meta-heuristic optimization algorithm known as bat algorithm to coordinate power oscillation damping controllers incorporated in renewable energy stations to ...
Samundra Gurung +2 more
doaj +1 more source
QuCardio: Application of Quantum Machine Learning for Detection of Cardiovascular Diseases
IEEE Access, 2023 This research is the first of its kind to leverage the power of Quantum Machine Learning (QML) to perform multi-class classification of Cardiovascular Diseases (CVDs).
Sharanya Prabhu +4 more
semanticscholar +1 more source
Data-centric approach for online P-margin estimation from noisy phasor measurements
Energy Reports, 2023 A new estimation method for load P-margin of transmission systems is proposed by using machine learning techniques. The estimation solution uses a reduced number of features as inputs to the machine learning algorithm and does not rely on power flow ...
Felipe Proença de Albuquerque +4 more
doaj +1 more source
Fast dynamic voltage security margin estimation: concept and development
IET Smart Grid, 2020 This study develops a machine learning-based method for a fast estimation of the dynamic voltage security margin (DVSM). The DVSM can incorporate the dynamic system response following a disturbance and it generally provides a better measure of security ...
Hannes Hagmar +3 more
doaj +1 more source
Practical CO2—WAG Field Operational Designs Using Hybrid Numerical-Machine-Learning Approaches
Energies, 2021 Machine-learning technologies have exhibited robust competences in solving many petroleum engineering problems. The accurate predictivity and fast computational speed enable a large volume of time-consuming engineering processes such as history-matching ...
Qian Sun +4 more
doaj +1 more source