A generative AI agent creates a realistic HAP propulsion power model including aerodynamic interference and enables a Q3E beamforming algorithm that improves QoS and energy efficiency.
Survey on near-space information networks: Channel modeling, networking, and transmission perspectives
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A two-step agentic system for extracting insights from VSM simulations achieves up to 86% accuracy with top LLMs by using progressive data discovery and slim context.
citing papers explorer
-
Generative AI Agent Empowered Power Allocation for HAP Propulsion and Communication Systems
A generative AI agent creates a realistic HAP propulsion power model including aerodynamic interference and enables a Q3E beamforming algorithm that improves QoS and energy efficiency.
-
Agentic Insight Generation in VSM Simulations
A two-step agentic system for extracting insights from VSM simulations achieves up to 86% accuracy with top LLMs by using progressive data discovery and slim context.