Abstract: Clustering time-series data has gained abundant popularity and has been widely used in diverse scientific areas. However, few studies have systematically addressed the ambiguity and ...
ABSTRACT: Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In ...
ABSTRACT: Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In ...
Temperature impacts every part of the world. Meteorological analysis and weather forecasting play a crucial role in sustainable development by helping reduce the damage caused by extreme weather ...
Time-series data—measurements collected at regular intervals, like stock prices or traffic flows—has become a key driver of intelligent decision-making systems across industries. From medical ...
Time-series data—measurements collected over time like stock prices or heart rates—plays a vital role in AI forecasting systems across industries. As these systems advance, the need for time-series ...
Solargis’ Evaluate 2.0 platform uses more granular time series data. Image: Solargis. For years, the solar industry has relied on Typical Meteorological Year (TMY) data as the standard for PV ...
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