Abstract: This paper introduces a hybrid algorithmic framework that merges Long Short-Term Memory (LSTM) networks, Genetic Algorithms (GA), Harmony Search (HS), and Cuckoo Search (CS) for detecting ...
The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
A new study suggests humans can sense hidden objects without touching them, by detecting faint movements in sand. This unexpected form of “remote touch” challenges traditional ideas about how the ...
Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...
Abstract: Credit card fraud detection is a critical task in financial systems, requiring effective algorithms to accurately classify transactions as fraudulent or non-fraudulent. This paper proposes a ...
new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript “Our brains are being melted by the algorithm.” [MUSIC PLAYING] “Attention is infrastructure.” “Those algorithms are ...
ABSTRACT: Forecasting fuel prices is a critical endeavor in energy economics, with significant implications for policy formulation, market regulation, and consumer decision-making. This study ...
ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
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