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What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Enhancing multilevel inverter performance through open-end winding motors and SVPWM series compensation. [PDF]

Sci Rep
Nalinakshan Latha S, Egeriose SK, Gopinathan S.   +2 more
europepmc   +1 more source

Research on precise estimation of line loss rate probability density based on bilateral total variation filtering algorithm. [PDF]

Sci Rep
Zhang J, Liu S, Feng C.
europepmc   +1 more source

Power system security and protection considering the integration of new energy power plants. [PDF]

Sci Rep
Wang S, Liu D, Su W, Zhang X, Hui S.
europepmc   +1 more source

Cortical latency predicts reading fluency from late childhood to early adolescence. [PDF]

Dev Cogn Neurosci
Wang F, Nguyen QTH, Kaneshiro B, Norcia AM, McCandliss BD.   +4 more
europepmc   +1 more source

Power quality enhancement using fractional order type-2 fuzzy SHAF optimized with hPSOFA algorithm. [PDF]

Sci Rep
Mishra AK, Mahakud JJ, Kamilla SK, Satapathy LM, Gantayet A, Choudhury S, Patra AK.   +6 more
europepmc   +1 more source

Structure-Function Dynamics in Healthy Cognitive Aging: A Graph Signal Processing Approach

Guichet C, Achard S, Mermillod M, Baciu M.   +3 more
europepmc   +1 more source

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Current Harmonics Suppression in IPMSMs Considering Rotational Harmonics

IEEE Transactions on Transportation Electrification
Current harmonics suppression exhibits advantages to improve the operational performance and lifetime of machines. Generally, it is recommended to transform current harmonics into the synchronous rotating frames (SRFs) and suppress those using PI or PR ...
Yilin Ma, Jingwei Lin, Huan Yang, Guangyuan Liu, Chunwei Song   +4 more
openaire   +2 more sources

Static-Errorless Deadbeat Predictive Current Control for PMSM Current Harmonics Suppression Based on Vector Resonant Controller

IEEE transactions on power electronics, 2023
The traditional deadbeat predictive current control (DPCC) is sensitive to the unmodeled disturbances in permanent magnet synchronous motor (PMSM) drives, including alternating current (ac) and direct current (dc) disturbances, which can lead to ...
Minghe Tian, Bo Wang, Yong Yu, Qinghua Dong, Dianguo Xu   +4 more
semanticscholar   +1 more source