Abstract: The need for renewable resource growth stems from the world's ever-growing energy consumption rate, finite supply of fossil fuels, and pollution. In order to accomplish the 2030 agenda and ...
The final, formatted version of the article will be published soon. {The paper discusses computational and numerical challenges that are associated with the truncation of the information and which ...
This project primarily used the small dataset with a high illicit ratio, which contains 5,078,345 financial transactions spanning 10 days.It effectively addresses challenges such as overlap and ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Abstract: Gaussian Mixture Function (GMF) is a widely utilized model for analyzing and elucidating experimental data in science and engineering, where the fitting of GMF with noisy observations is ...
This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
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