Prediction of ferrous scrap price: Neural network model application-Reference-Cited by-同舟云学术

Prediction of ferrous scrap price: Neural network model application

Published:2018 Issue: Volume: Page:
ISSN:0094-243X
Container-title:AIP Conference Proceedings
language:
Short-container-title:

Author:

Panachev A. A.,Komotskiy E. I.,Berg D. B.,Atanasova T. B.,Khorev O. E.

Publisher

Author(s)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5079111

Reference10 articles.

1. Denisenko M., Palicin V., “Features of forecasting prices of ferrous metallurgy enterprises production”, National metallurgy, №5, 2003.

2. Kosovceva T.R., Belyaeva V.V., The technologies of processing economical information. Adaptive forecasting methods. Education material (ITMO University, St. Petersburg, 2016).

3. Kingma D.P., Lei Ba J., Adam: a method for stochastic optimization, 21.10.2017, available at: https://arxiv.org/pdf/1412.6980.pdf.

4. CIN classification and prediction using machine learning methods

5. O.I. Nikonov, M.A. Medvedeva, F.P. Chernavin, “Using the Committee Machine Method to Forecasting on the FOREX”, Proceedings, Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI 2015) (Conference Publishing Services (CPS), 2015), pp. 240–243.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on Cement Price Fluctuation Prediction Based on EEMD-ARIMA;Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate;2023

2. On the prediction of dispenser status in ATM using gradient boosting method;PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2019 (ICCMSE-2019);2019