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Authors: Matteo Hessel 1 ; Francesco Borgatelli 2 and Fabio Ortalli 2

Affiliations: 1 Politecnico di Milano, Italy ; 2 TXT e-solutions, Italy

ISBN: 978-989-758-038-3

Keyword(s): Model Tuning, Screening, Optimization, Machine-Learning, Adaptive Hill-Climbing, Sequential Masking.

Related Ontology Subjects/Areas/Topics: Computer Simulation Techniques ; Dynamical Systems Models and Methods ; Formal Methods ; Mathematical Simulation ; Non-Linear Systems ; Optimization Issues ; Simulation and Modeling ; Simulation Tools and Platforms

Abstract: The aim of this paper is to describe a novel methodology for model-design and tuning in computer simulations, based on automatic parameter screening and optimization. Simulation requires three steps: mathematical modelling, numerical solution, and tuning of the model’s parameters. We address Tuning because, at the state-of-the-art, the development of life-critical simulations requires months to appropriately tune the model. Our methodology can be split in Screening (identification of the relevant parameters to simulate a system) and Optimization (search of optimal values for those parameters). All techniques are fully general, because they leverage ideas from Machine-Learning and Optimization Theory to achieve their goals without directly analysing the simulator’s mathematical model. Concerning screening, we show how Machine-Learning algorithms, based on Neural Networks and Logistic Regression, can be used for ranking the parameters according to their relevance. Concerning optimizatio n, we describe two algorithms: an adaptive hill-climbing procedure and a novel strategy, specific for model tuning, called sequential masking. Eventually, we show the performances achieved and the impact on the time and effort required for tuning a helicopter flight-simulator, proving that the proposed techniques can significantly speed-up the process. (More)

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Paper citation in several formats:
Hessel, M.; Borgatelli, F. and Ortalli, F. (2014). A Novel Approach to Model Design and Tuning through Automatic Parameter Screening and Optimization - Theory and Application to a Helicopter Flight Simulator Case-study.In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-038-3, pages 24-35. DOI: 10.5220/0005022600240035

@conference{simultech14,
author={Matteo Hessel. and Francesco Borgatelli. and Fabio Ortalli.},
title={A Novel Approach to Model Design and Tuning through Automatic Parameter Screening and Optimization - Theory and Application to a Helicopter Flight Simulator Case-study},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2014},
pages={24-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005022600240035},
isbn={978-989-758-038-3},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - A Novel Approach to Model Design and Tuning through Automatic Parameter Screening and Optimization - Theory and Application to a Helicopter Flight Simulator Case-study
SN - 978-989-758-038-3
AU - Hessel, M.
AU - Borgatelli, F.
AU - Ortalli, F.
PY - 2014
SP - 24
EP - 35
DO - 10.5220/0005022600240035

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