참고문헌
- S. L. Mok, and C. K. Kwong, F. Grasser, A. D'Arrigo, and S. Colombi, "Application of artificial neural network and fuzzy logic in a case-based system for initial process parameter setting of injection molding" Journal of Intelligent Manufacturing, vol. 13, no. 3, pp. 165-176, (2002). https://doi.org/10.1023/A:1015730705078
- X. Zhou, U. Zhang, T. Mao, and H. Zhou, "Monitoring and dynamic control of quality stability for injection moldingprocess" Journal of Materials Processing Tech, vol. 249, pp. 358-366, (2017). https://doi.org/10.1016/j.jmatprotec.2017.05.038
- J. Y. Chen, K. J. Yang, S. M. Huang, "Online quality monitoring of molten resin in injection molding." International Journal of Heat and Mass Transfer, vol. 122, pp. 681-693, (2018). https://doi.org/10.1016/j.ijheatmasstransfer.2018.02.019
- B. H. M. Sadeghi, "A BP-neural network predictor model for plastic injection molding process" Journal of materials processing technology, vol. 103, No. 3, pp. 411-416, (2001). https://doi.org/10.1016/S0924-0136(00)00498-2
- S. Kening, A. Ben-David, M. Orner, and A. Sadeh, "Control of properties in injection molding by neural networks." Applications of Artificial Intelligence, vol. 14, No. 6, pp. 819-823, (2001). https://doi.org/10.1016/S0952-1976(02)00006-4
- B. Ozcelik, and T. Erzurumlu, "Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm" Journal of materials processing technology, vol. 171, No. 3, pp. 437-445, (2006). https://doi.org/10.1016/j.jmatprotec.2005.04.120
- C. Ozek, and Y. Celik, "Calculating molding parameters in plastic injection molds with ANN and developing software" Materials and Manufacturing Processes, vol. 27, No. 2, pp. 160-168, (2012). https://doi.org/10.1080/10426914.2011.560224
- S. Shanmuganathan, "Artificial neural network modelling: An introduction. In Artificial neural network modelling" Springer:German, pp. 1-14, (2016).
- Y. J. Kim, H. J. Kim, J. Y. Ha n, and S. Lee, "Classification of Tire Tread Wear Using Accelerometer Signals through an Artificial Neural Network", Journal of the Korean Society of Industry Convergence, Vol. 23, No. 2, pp. 163-171, (2020).
- P. Balaprakash, M. Salim, and T. D. Uram, "Deep Hyper: Asynchronous Hyperparamter Search for Deep Neural Networks", IEEE 25th International Conference on High Performance Computing, pp. 42-51, (2018).
- D. C. Yang, J. H. Lee, K. H. Yoon, and J. S. Kim, "A Study on the Prediction of Optimized Injection Molding Condition using Artificial Neural Network (ANN)" Transactions of Materials Processing, Vol. 29, No. 4, pp. 1-14, (2020).
- T. S. Jin, "Feature Extraction Using Convolution Neural Networks for Random Translation" Journal of the Korean Society of Industry Convergence, Vol. 23, No. 3, pp. 515-521, (2020). https://doi.org/10.21289/KSIC.2020.23.3.515
- H. K. Cho, and J. S. Lee, " A Study on the Rainfall Forecasting Using Neural Network Model In Nakdong River Basin - A Comparison with Multivariate Model" Journal of the Korean Society of Industry Convergence, Vol. 2, No. 2, pp. 51-59, (1999).
- J. H. Lee, K. H. Yoon, J. S. Kim, S. Y. Kim, and H. Y. Lim, "The Effect of Property Change of Resin on Injection Molded Part", Transactions of Materials Processing, Vol. 29, No. 4, pp. 1-14, (2020).
- P. Zhao, Z. Dong, J. Zhang, Y. Zhang, M. Cao, Z. Zhu, H. Zhou, and J. Fu, "Optimization of Injection-Molding Process Parameters for Weight Control: Converting Optimization Problem to Classification Problem", Advances in Polymer Technology, Vol. 2020, pp. 1-9, (2020)
- D. P. Kingma, and J. Ba, "ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION", The 3rd International Conference for Learning Representations (arXiv preprint arXiv:1412.6980), (2015)