Predictive modeling and atomic-scale control are reducing development time for advanced materials, also increasing precision, functionality, and efficiency.
This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...
The transformer-based model is being developed to help organizations—most notably in the finance industry—dig deeper into their data.
Abstract: In this paper, a model predictive based minimum DC-link voltage control (MP-mDVC) method is proposed to enhance both the reliability and dynamic performance of grid-connected converters ...
Abstract: Explicit model predictive direct speed control (EMP-DSC) for permanent magnet synchronous motors can achieve excellent control performance with high dynamics and high precision. However, the ...
When experimental results don't match scientists' predictions, it's usually assumed that the predictions were wrong. But new research into materials that pull carbon dioxide directly from the air ...
With the wealth of data institutions have at their disposal, and with the emergence of more sophisticated analytics and decision-making capabilities, institutions have an opportunity to shift from ...
ACA Research Group, Faculty of Business Studies, University of Vaasa, Vaasa, Finland. The content of this paper is divided into four short sections. In the first section, the motivation and content of ...
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