Multi-output regression using polygon generation and conditional generative adversarial networks-Reference-Cited by-同舟云学术

Multi-output regression using polygon generation and conditional generative adversarial networks

Published:2022-10 Issue: Volume:203 Page:117288
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Elhefnawy Mohamed,Ouali Mohamed-Salah,Ragab Ahmed

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference68 articles.

1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., … Zheng, X. (2015). TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. Retrieved from https://www.tensorflow.org/.

2. Aggarwal, K., Kirchmeyer, M., Yadav, P., Keerthi, S. S., & Gallinari, P. (2019). Benchmarking Regression Methods: A comparison with CGAN. (May). Retrieved from http://arxiv.org/abs/1905.12868.

3. Amazouz, M. (2015). Improving Process Operation Using the Power of Advanced Data Analysis. Retrieved from https://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/canmetenergy/files/pubs/EXPLORE-brochure_ EN.pdf.

4. Anaconda Software Distribution. (2020). Anaconda Documentation. Retrieved from https://docs.anaconda.com/.

5. Key performance indicators for energy management in the Swedish pulp and paper industry;Andersson;Energy Strategy Reviews,2019

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