Stacked encoded cascade error feedback deep extreme learning machine network for manufacturing order completion time
Author:
Funder
King Fahd University of Petroleum and Minerals
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s10845-023-02303-0.pdf
Reference86 articles.
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3. Arumugam, D., & Kiran, R. (2023). Interpreting denoising autoencoders with complex perturbation approach. Pattern Recognition, 136, 109212. https://doi.org/10.1016/j.patcog.2022.109212
4. Chang, C.-C., & Lin, C.-J. (2011). LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3), 1–27. https://doi.org/10.1145/1961189.1961199
5. Chen, T., & Guestrin, C. (2016). XGBoost: a scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 785–794). https://doi.org/10.1145/2939672.2939785
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