The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Prever o preço futuro das commodities é uma tarefa desafiadora. Apresentamos um algoritmo para prever a tendência do preço futuro de commodities com base em um tipo de estruturação de dados e rede neural de retropropagação. A volatilidade aleatória dos futuros pode ser filtrada nos dados estruturantes. Além disso, não está restrito ao tipo de contrato futuro. Experimentos mostram que o algoritmo pode atingir 80% de precisão na previsão de tendências de preços.
Weijun LU
BUPT
Chao GENG
BUPT
Dunshan YU
PUK
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Weijun LU, Chao GENG, Dunshan YU, "A New Method for Futures Price Trends Forecasting Based on BPNN and Structuring Data" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 9, pp. 1882-1886, September 2019, doi: 10.1587/transinf.2018EDL8190.
Abstract: Forecasting commodity futures price is a challenging task. We present an algorithm to predict the trend of commodity futures price based on a type of structuring data and back propagation neural network. The random volatility of futures can be filtered out in the structuring data. Moreover, it is not restricted by the type of futures contract. Experiments show the algorithm can achieve 80% accuracy in predicting price trends.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8190/_p
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@ARTICLE{e102-d_9_1882,
author={Weijun LU, Chao GENG, Dunshan YU, },
journal={IEICE TRANSACTIONS on Information},
title={A New Method for Futures Price Trends Forecasting Based on BPNN and Structuring Data},
year={2019},
volume={E102-D},
number={9},
pages={1882-1886},
abstract={Forecasting commodity futures price is a challenging task. We present an algorithm to predict the trend of commodity futures price based on a type of structuring data and back propagation neural network. The random volatility of futures can be filtered out in the structuring data. Moreover, it is not restricted by the type of futures contract. Experiments show the algorithm can achieve 80% accuracy in predicting price trends.},
keywords={},
doi={10.1587/transinf.2018EDL8190},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - A New Method for Futures Price Trends Forecasting Based on BPNN and Structuring Data
T2 - IEICE TRANSACTIONS on Information
SP - 1882
EP - 1886
AU - Weijun LU
AU - Chao GENG
AU - Dunshan YU
PY - 2019
DO - 10.1587/transinf.2018EDL8190
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2019
AB - Forecasting commodity futures price is a challenging task. We present an algorithm to predict the trend of commodity futures price based on a type of structuring data and back propagation neural network. The random volatility of futures can be filtered out in the structuring data. Moreover, it is not restricted by the type of futures contract. Experiments show the algorithm can achieve 80% accuracy in predicting price trends.
ER -