Application of Machine Learning Method in Simulation Model Validation

DOI

10.2991/eame-18.2018.48How to use a DOI?

Keywords

machine learning; simulation validation; error estimate; data composition

Abstract

There exists distrust in simulation validation all the time. A quantitative approach is proposed to obtain measurable, comparable judgments of simulation correctness. The commonality between machine learning and simulation model validation is analyzed. We focus on the idea of applying cross validation in the area of simulation validation. Based on cross validation, a strategy is proposed to predict the fit of a simulation model to a validation set. Scaling factor is then introduced into the approach to improve its efficiency. The approach is applied in a simulation system to verify the usefulness of the approach proposed. The result shows it is convinient to get an effective estimate of correctness of simulation models with the method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Qi Lin
AU  - Yong Chen
PY  - 2018/06
DA  - 2018/06
TI  - Application of Machine Learning Method in Simulation Model Validation
BT  - Proceedings of the 2018 3rd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2018)
PB  - Atlantis Press
SP  - 229
EP  - 233
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-18.2018.48
DO  - 10.2991/eame-18.2018.48
ID  - Lin2018/06
ER  -