Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
Abstract: To address the limitations of slow convergence, low accuracy, and local optima entrapment in the Archimedes Optimization Algorithm (AOA), we propose a multi-strategy enhanced ...
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