This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
The American Control Conference (ACC), the annual conference of the American Automatic Control Council (AACC), will offer ...
Better understanding of the design, implementation and operation of these cyber-physical systems can enable optimized process ...
Economic models used by governments, central banks and investors are increasingly understating physical climate risk because ...
Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized energy management. Yet as renewable penetration rises, maintaining stable ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...
Electra announces a major milestone with the successful validation of its EVE‑Ai™ Adaptive Controls platform, enabling ...
In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...
BackgroundAs pivotal drivers of smart cities, mega-mobility systems integrate large-scale transportation networks, communication nodes, and energy ...
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