AI Learns to Hunt Radio Spectrum: War-Strategy Boost for Cognitive Networks
Researchers at SASTRA Deemed University have combined deep reinforcement learning with an adaptive war strategy to let cognitive radio networks ...
Researchers at SASTRA Deemed University have combined deep reinforcement learning with an adaptive war strategy to let cognitive radio networks ...
Researchers in Tehran have developed SM-SFLA, a structured migration variant of the shuffled frog leaping algorithm that rebalances virtual machines ...
A University of Bath feasibility study finds that swapping standardized hydrogen tanks instead of pumping gas could cut refueling infrastructure ...
Researchers have combined a digital twin simulation platform with federated multi-agent reinforcement learning to optimize resource allocation across satellite, UAV, ...
A new study shows that microwave drying is the most energy-efficient method for Acorus calamus rhizomes, with slice thickness and ...
A nationwide modeling study combining Thompson's drying model, geospatial analysis, and neural networks estimates that low-temperature soybean drying in Brazil ...
Researchers have developed a hybrid Greater Cane Mayfly Algorithm that improves routing, quality of service, and resource efficiency in mobile ...
Researchers have developed a multi-objective path-planning framework that uses Voronoi partitioning and urgency-based routing to extend the lifetime of rechargeable ...
Thai researchers show that superheated steam fluidized bed drying cuts drying time and energy use while producing whiter coconut press ...
A new reinforcement learning framework called FLASH-DRM selects the most valuable devices for each federated learning round, improving accuracy, latency ...
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© 2025 Scienmag - Science Magazine