|
[1]Basil Kahan, 2000, Ottmar Mergenthaler – The Man and his Machine, Oak Knoll Press, New Castle (DE). [2]Liu, Wen-Hai, 2009, The Progress and Trends of Die Casting Process and Application. [3]E. Paul; et al. 2003, Ronald A. Materials and Processes in Manufacturing (9th ed.) , Wiley. [4]Hai-Hong Li, et al. 2005, “Study and Development of SSP Die-casting Thixomolding of Magnesium Alloys.” Hot Working Technology, pp. 59-61, October. [5]Hanxue Cao, et al. 2017 “The influence of different vacuum degree on the porosity and mechanical properties of aluminum die casting,” Vacuum, Vol. 146, pp. 278-281. [6]K.Ch. Apparao, Anil Kumar Birru, 2017 “Optimization of Die casting process based on Taguchi approach,” Materials Today: Proceedings, Vol 4 ,pp. 1852-1859. [7]K.D.V. Yarlagadda, Eric Cheng Wei Chiang, 1999, “A neural network system for the prediction of process parameters in pressure die casting.” Journal of Materials Processing Technology, Vol. 89-90, pp. 583-590, May. [8]S.H. Mousavi Anijdan, et al. 2006, “Using genetic algorithm and artificial neural network analyses to design an Al–Si casting alloy of minimum porosity.” Materials & Design, Vol. 27, pp. 605-609, Issue 7. [9]Bekir Aksoy, Murat Koru, 2020 “Estimation of Casting Mold Interfacial Heat Transfer Coefficient in Pressure Die Casting Process by Artificial Intelligence Methods.” Arabian Journal for Science and Engineering, Vol. 45, pp.8696-8980, November. [10]R. Kohavi, 1995, “A study of cross-validation and bootstrap for accuracy estimation and model selection.” IJCAI'95: Proceedings of the 14th international joint conference on Artificial intelligence, Vol. 2. pp. 1137-1143, 20 August [11]R. A. Tuhin, et al. 2019 “An Automated System of Sentiment Analysis from Bangla Text using Supervised Learning Techniques.” 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS), pp. 360-364, 23-25 Feb. [12]R. W. Schafer, 2011, “What Is a Savitzky-Golay Filter Filter? [Lecture Notes],” IEEE Signal Processing Magazine, Vol. 28, pp. 111-117, July. [13]R. Cao, et al. 2018, “A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay Filter filter,” Remote Sensing of Environment, Vol. 217, pp. 244-257, November. [14]B. J. Odelson, et al. 2006, “A new autocovariance least-squares method for estimating noise covariances,” Automatica, Vol 42, pp. 303-308, February. [15]C. M. Borror, et al. 1999, “Robustness of the EWMA Control Chart to Non-Normality.” Journal of Quality Technology, Vol 31, pp. 309-316. [16]J. Shlens, 2014, “A Tutorial on Principal Component Analysis,” arXiv:1404.1100, Machine Learning. [17]D. Granato, et al. 2018, “Use of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for multivariate association between bioactive compounds and functional properties in foods: A critical perspective,” Trends in Food Science & Technology, Vol. 72, pp. 83-90. [18]A. Hyvärinen, E. Oja, 2000, “Independent component analysis: algorithms and applications,” Neural Networks, Vol. 13, Issues 4-5, pp. 411-430, June [19]D. W. Hosmer, 2013, Applied Logistic Regression, A Wiley-Interscience Publication, New York. [20]L.M. Manevitz, M. Yousef, 2001,“ One-Class SVMs for Document Classification,” Machine Learning Research, Vol. 02, pp. 139-154, January. [21]I. J. Goodfellow, et al. 2014, “Generative Adversarial Networks,” Advances in Neural Information Processing Systems, Vol. 27 [22]T. Chen, C. Guestrin, 2016, “XGBoost: A Scalable Tree Boosting System,” In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, pp.785-794, New York, NY, USA. [23]A. Ogunleye, Q. -G. Wang, 2020, “XGBoost Model for Chronic Kidney Disease Diagnosis,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 17, no. 6, pp. 2131-2140, December. [24]Breiman, Leo, 2001, “Random Forests,” Machine Learning, Vol. 45, pp.5-32, October. [25]R. Katuwal, et al. 2020, “Heterogeneous oblique random forest,” Pattern Recognition, Vol. 99, March. [26]Wikipedia Random forest. [Online] Available:https://en.wikipedia.org/wiki/Random_forest [27]O. I. Abiodun, et al. 2018, “State-of-the-art in artificial neural network applications: A survey,” Heliyon, Volume 4, Issue 11. [28]Y. Lin, et al. 2020 “Threats of Adversarial Attacks in DNN-Based Modulation Recognition,” IEEE Conference on Computer Communications, [29]V. Sze, et al. 2017, “Efficient Processing of Deep Neural Networks: A Tutorial and Survey,” Proceedings of the IEEE, Vol. 105, no. 12, pp. 2295-2329., December. [30]A. L. Maas, et al. 2013, “Rectifier nonlinearities improve neural network acoustic models,” International Conference on Machine Learning (ICML), USA. [31]G. E. Hinton, et al. 2012, “Improving neural networks by preventing co-adaptation of feature detectors,” arXiv:1207.0580, Neural and Evolutionary Computing.
|