Gold price forecasting research based on an improved online extreme learning machine algorithm

Accurate gold price prediction is highly essential for economic and currency markets. Thus, the intelligence prediction models need to be applied to price prediction. On the basis of long-term collected daily gold, the study proposes a novel genetic algorithm regularization online extreme learning m...

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Vydáno v:	Journal of ambient intelligence and humanized computing Ročník 11; číslo 10; s. 4101 - 4111
Hlavní autoři:	Weng, Futian, Chen, Yinhao, Wang, Zheng, Hou, Muzhou, Luo, Jianshu, Tian, Zhongchu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2020 Springer Nature B.V
Témata:	Accuracy Artificial Intelligence Artificial neural networks Autoregressive models Computational Intelligence Crude oil Crude oil prices Distance learning Engineering Forecasting Genetic algorithms Gold Machine learning Mean square errors Neural networks Optimization Original Research Prediction models Regularization Research methodology Robotics and Automation Time series User Interfaces and Human Computer Interaction Variables Wavelet transforms Online learning machine AIC criterion Genetic algorithm Gold price forecast
ISSN:	1868-5137, 1868-5145
On-line přístup:	Získat plný text
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