Digital Twin of the Ocean is a continuously updated virtual counterpart of the real ocean that exchanges data in real time ...
Abstract: Time series forecasting task aims at predicting future time series signal given historical time series observations. This letter investigates time series signal modeling and forecasting from ...
In the world around us, many things exist in the context of time: a bird's path through the sky is understood as different positions over a period of time, and conversations as a series of words ...
Abstract: The rise of decentralized energy sources and renewables demands advanced grid planning, with short-term load forecasting (STLF) playing a crucial role. Energy demand in smart grids is highly ...
In the world around us, many things exist in the context of time: a bird’s path through the sky is understood as different positions over a period of time, and conversations as a series of words ...
ABSTRACT: The application of artificial intelligence in stock price forecasting is an important area of research at the intersection of finance and computer science, with machine learning techniques ...
Until recently, using machine learning for a specific task meant training the system on vast amounts of relevant data. The same was true for data representing a system that changes over time, says SFI ...
Successful test results of a new machine learning (ML) technique developed at Georgia Tech could help communities prepare for extreme weather and coastal flooding. The approach could also be applied ...
ABSTRACT: Time series forecasting is essential for generating predictive insights across various domains, including healthcare, finance, and energy. This study focuses on forecasting patient health ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback