Evaluation of interval regression analysis for uncertain resistance spot welding quality data

References

• Abdel-Tawab, K., and A. K. Noor. 1999. “Uncertainty Analysis of Welding Residual Stress Fields.” Computer Methods in Applied Mechanics and Engineering 179 (3–4): 327–344. doi:10.1016/S0045-7825(99)00045-6.
   Web of Science ®Google Scholar
• Chung, W. 2012. “Using the Fuzzy Linear Regression Method to Benchmark the Energy Efficiency of Commercial Buildings.” Applied Energy 95: 45–49. doi:10.1016/j.apenergy.2012.01.061.
   Web of Science ®Google Scholar
• Hong, D. H., and C. Hwang. 2005. “Interval Regression Analysis Using Quadratic Loss Support Vector Machine.” IEEE Transactions on Fuzzy Systems 13 (2): 229–237. doi:10.1109/TFUZZ.2004.840133.
   Web of Science ®Google Scholar
• Huang, C.-H. 2012. “A Reduced Support Vector Machine Approach for Interval Regression Analysis.” Information Sciences 217: 56–64. doi:10.1016/j.ins.2012.06.030.
   Web of Science ®Google Scholar
• Hwang, C., D. H. Hong, and K. H. Seok. 2006. “Support Vector Interval Regression Machine for Crisp Input and Output Data.” Fuzzy Sets and Systems 157 (8): 1114–1125. doi:10.1016/j.fss.2005.09.008.
   Web of Science ®Google Scholar
• Ishibuchi, H., and H. Tanaka. 1992. “Fuzzy Regression Analysis Using Neural Networks.” Fuzzy Sets and Systems 50 (3): 257–265. doi:10.1016/0165-0114(92)90224-R.
   Web of Science ®Google Scholar
• Ishibuchi, H., H. Tanaka, and H. Okada. 1993. “An Architecture of Neural Networks with Interval Weights and Its Application to Fuzzy Regression Analysis.” Fuzzy Sets and Systems 57 (1): 27–39. doi:10.1016/0165-0114(93)90118-2.
   Web of Science ®Google Scholar
• Itoh, H., J. Katsuyama, and K. Onizawa. 2008. “A Probabilistic Evaluation Model for Welding Residual Stress Distribution at Piping Joint in Probabilistic Fracture Mechanics Analysis.” In ASME 2008 Pressure Vessels and Piping Conference, 1137–1142.
   Google Scholar
• Jeng, J.-T., C.-C. Chuang, and S.-F. Su. 2003. “Support Vector Interval Regression Networks for Interval Regression Analysis.” Fuzzy Sets and Systems 138 (2): 283–300. doi:10.1016/S0165-0114(02)00570-5.
   Web of Science ®Google Scholar
• Kim, I.-S., Y. J. Jeong, C. W. Lee, and P. K. D. V. Yarlagadda. 2003. “Prediction of Welding Parameters for Pipeline Welding Using an Intelligent System.” The International Journal of Advanced Manufacturing Technology 22 (9–10): 713–719. doi:10.1007/s00170-003-1589-y.
   Web of Science ®Google Scholar
• Kim, K.-Y., J. Park, and R. Sohmshetty. 2016. “Prediction Measurement with Mean Acceptable Error for Proper Inconsistency in Noisy Weldability Prediction Data.” Robotics and Computer-Integrated Manufacturing43: 18-29.
   Google Scholar
• Lu, W., Y. M. Zhang, and W.-Y. Lin. 2004. “Nonlinear Interval Model Control of Quasi-Keyhole Arc Welding Process.” Automatica 40 (5): 805–813. doi:10.1016/j.automatica.2003.11.017.
   Web of Science ®Google Scholar
• Onizawa, K., H. Nishikawa, and H. Itoh. 2010. “Development of Probabilistic Fracture Mechanics Analysis Codes for Reactor Pressure Vessels and Piping Considering Welding Residual Stress.” International Journal of Pressure Vessels and Piping 87 (1): 2–10. doi:10.1016/j.ijpvp.2009.11.011.
   Web of Science ®Google Scholar
• Ouafi, E., A. R. Bélanger, and J. F. Méthot. 2011. “Artificial Neural Network-Based Resistance Spot Welding Quality Assessment System.” Revue De Métallurgie 108 (06): 343–355. doi:10.1051/metal/2011066.
   Google Scholar
• Pal, S., S. K. Pal, and A. K. Samantaray. 2008. “Artificial Neural Network Modeling of Weld Joint Strength Prediction of a Pulsed Metal Inert Gas Welding Process Using Arc Signals.” Journal of Materials Processing Technology 202 (1–3): 464–474. doi:10.1016/j.jmatprotec.2007.09.039.
   Web of Science ®Google Scholar
• Park, J., and K.-Y. Kim. 2016. “Instance Variant Nearest Neighbor Using Particle Swarm Optimization for Function Approximation.” Applied Soft Computing 40: 331–341. doi:10.1016/j.asoc.2015.10.055.
   Web of Science ®Google Scholar
• Park, J., and K.-Y. Kim. 2017. “Prediction Modeling Framework with Bootstrap Aggregating for Noisy Resistance Spot Welding Data.” ASME Journal of Manufacturing Science and Engineering 139: 101003. doi:10.1115/1.4036787.
   PubMed Web of Science ®Google Scholar
• Park, J., K.-Y. Kim, and R. Sohmshetty. 2014. “Towards Proper-Inconsistency in Weldability Prediction Using K-Nearest Neighbor Regression and Generalized Regression Neural Network with Mean Acceptable Error.” In Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, 395.
   Google Scholar
• Santos, T. O., R. B. Caetano, J. M. Lemos, and F. J. Coito. 2000. “Multipredictive Adaptive Control of Arc Welding Trailing Centerline Temperature.” IEEE Transactions on Control Systems Technology 8 (1): 159–169. doi:10.1109/87.817701.
   Web of Science ®Google Scholar
• Tanaka, H., and H. Lee. 1998. “Interval Regression Analysis by Quadratic Programming Approach.” IEEE Transactions on Fuzzy Systems 6 (4): 473–481. doi:10.1109/91.728436.
   Web of Science ®Google Scholar
• Tanaka, H., I. Hayashi, and J. Watada. 1989. “Possibilistic Linear Regression Analysis for Fuzzy Data.” European Journal of Operational Research 40 (3): 389–396. doi:10.1016/0377-2217(89)90431-1.
   Web of Science ®Google Scholar
• Tanaka, H., S. Uejima, and K. Asai. 1980. “Fuzzy Linear Regression Model.” IEEE Transactions on Systems Man and Cybernetics 10 (4): 2933–2938.
   Google Scholar
• Yin, S.-A., R.-F. Chang, and C.-N. Lu. 2003. “Reliability Worth Assessment of High-Tech Industry.” IEEE Transactions on Power Systems 18 (1): 359–365. doi:10.1109/TPWRS.2002.807079.
   Web of Science ®Google Scholar
• Zhang, Y. M., E. Liguo, and B. L. Walcott. 2002. “Robust Control Of Pulsedgas Metal Arc Welding.” Asme Journal Of Dynamic Systems, Measurement, And Control 124 (2): 281–289.
   Web of Science ®Google Scholar