Towards On-Board Implementation of ML-Based Helicopter Weight Estimator

Author1, Author2, Author3, Author4, Author5

machine learningweight estimationaviationrecurrent neural networks

2608.19210

Builder Relevance

80%

2h ago

Abstract

This paper presents a novel supervised Machine Learning model for estimating helicopter weight during takeoff using extensive datasets.

Reality Card

Core Claim

The implementation of a long short-term memory recurrent neural network for helicopter weight estimation is verified on legacy avionics computers, making it suitable for critical on-board functions.

Method / Result

Demonstrated on legacy avionics computers, ensuring compatibility with existing systems.

Limitations

The study may face challenges in replicating results across different helicopter models or configurations.

Paper to code

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