Bayesian Classifier Based Validation Method for Multivariate Systems Chongqing University

Format:

Conference/Event

Author/Creator:

Yang, Yang, author.

Contributor:

Hu, Jie

Zhan, Zhenfei

Zheng, Kai

Conference Name:

SAE 2016 World Congress and Exhibition (2016-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2016

Summary:

Simulation models based design has become the common practice in automotive product development. Before applying these models in practice, model validation needs to be conducted to assess the validity of the models by comparing model predictions with experimental observations. In the validation process, it is vital to develop appropriate validation metrics for intended applications. When dealing with multivariate systems, comparisons between model predictions and test data with multiple responses would lead to conflicting decisions. To address this issue, this paper proposed a Bayesian classifier based validation method. With the consideration of both error rate and confidence in hypothesis testing, Bayesian classifier is developed for decision making. The process of validation is implemented on a real-world vehicle design case. The results show the proposed method's potential in practical application

Notes:

Vendor supplied data

Publisher Number:

2016-01-0284

Access Restriction:

Restricted for use by site license