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SBIR/STTR

Auto-Suggest Capability via Machine Learning in SMART NAS, Phase I

Completed Technology Project

Project Introduction

We build machine learning capabilities that enables the Shadow Mode Assessment using Realistic Technologies for the NAS (SMART NAS) system to synthesize, optimize, and "auto-suggest" optimized Traffic Management Initiatives (TMIs). Multi Level Multi View (MLMV) machine learning is used to identify similar historical situations (days, scenarios, or airport conditions) in the NAS. TMIs used in historically similar situations are locally modified to optimize the parameters of the TMI to be used in the current day situation. SMART NAS is used to evaluate TMIs and to present fast time simulations to the end user to review the TMI and associated performance metrics before implementation. More »

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Primary U.S. Work Locations and Key Partners

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Project Duration

Technology Maturity (TRL)

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