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Automotive Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2014

Iowa State University

Center for e-Design Proceedings

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Full-Text Articles in Automotive Engineering

Towards Proper-Inconsistency In Weldability Prediction Using K-Nearest Neighbor Regression And Generalized Regression Neural Network With Mean Acceptable Error, Junheung Park, Kyoung-Yun Kim, Raj Sohmshetty Jan 2014

Towards Proper-Inconsistency In Weldability Prediction Using K-Nearest Neighbor Regression And Generalized Regression Neural Network With Mean Acceptable Error, Junheung Park, Kyoung-Yun Kim, Raj Sohmshetty

Center for e-Design Proceedings

A significant inconsistency problem exists in the quality of resistance spot welding, and yet it offers various advantages in production. These inconsistent welding data can be eliminated using anomaly detection or instance selection methods. However, in the weldability prediction problem, this inconsistency we refer to as proper-inconsistency, may not be eliminated since it can be used to extract additional information. In this research, we examine the effects of this inconsistency on prediction performance using two machine learning methods, k-Nearest Neighbors (kNN) regression and Generalized Regression Neural Network, in order to identify an approach towards tackling the proper-inconsistency problem in weldability ...