Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat-Reference-Cited by-同舟云学术

Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat

Published:2022-07 Issue:3 Volume:29 Page:169-181
ISSN:1055-615X
Container-title:Intelligent Systems in Accounting, Finance and Management
language:en
Short-container-title:Intell Sys Acc Fin Mgmt

Author:

Xu Xiaojie¹^ORCID,Zhang Yun¹

Affiliation:

1. North Carolina State University Raleigh NC USA

Publisher

Wiley

Subject

Finance,General Business, Management and Accounting

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/isaf.1519

Reference81 articles.

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2. Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: A new hybrid copula-driven approach

3. A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizer

4. Real-Time Grain Commodities Price Predictions in South Africa: A Big Data and Neural Networks Approach

5. Baghirli O.(2015).Comparison of lavenberg‐marquardt scaled conjugate gradient and bayesian regularization backpropagation algorithms for multistep ahead wind speed forecasting using multilayer perceptron feedforward neural network.

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