Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Harvard University is providing seven free online courses in data science, each running for eight to nine weeks and requiring ...

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

Abstract: In modern era, time series forecasting plays a crucial role in Solar Power Generation (SPG), by allowing the prediction of future energy output using past power and weather data for grid ...

1 Department of Physiology, School of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China 2 School of Public Health, Kunming Medical University, Kunming, Yunnan, China Objective: The ...

. ├── main.py # Streamlit application ├── src/ │ ├── models/ │ │ ├── rough_set_fuzzy.py # Rough set fuzzy logic model │ │ └── intuitionistic_fuzzy.py # Intuitionistic fuzzy logic model │ └── utils/ │ ...

20 Superstars, two matches, one word... WarGames! The annual Survivor Series Premium Live Event returns on Saturday, November 29, when WWE takes over Petco Park and transforms the home of Major League ...

In this tutorial, we build an advanced agentic AI system that autonomously handles time series forecasting using the Darts library combined with a lightweight HuggingFace model for reasoning. We ...

1 Faculty of Electrical Technology and Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia. 2 Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...