We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...
The final, formatted version of the article will be published soon. Background Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among ...
Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...
Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...
A decorated UVA engineer collects early-career honors for his leadership and contributions to the data mining field.
ABSTRACT: Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and ...
Abstract: The increasing penetration of inverter-based distributed generation (DG) into power grids improves access to electricity and provides a significant possibility for decarbonization. However, ...
Abstract: This research investigates the transformative role of machine learning (ML) in automating knowledge extraction (AKE) from unstructured text data, a critical challenge in the era of big data.
You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
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