A Novel Hybrid Deep Learning Model for Sugar Price Forecasting Based on Time Series Decomposition

Abstract

Sugar price forecasting has attracted extensive attention from policymakers due to its significant impact on people’s daily lives and markets. In this paper, we present a novel hybrid deep learning model that utilizes the merit of a time series decomposition technology empirical mode decomposition (EMD) and a hyperparameter optimization algorithm Tree of Parzen Estimators (TPEs) for sugar price forecasting. The effectiveness of the proposed model was implemented in a case study with the price of London Sugar Futures. Two experiments are conducted to verify the superiority of the EMD and TPE. Moreover, the specific effects of EMD and TPE are analyzed by the DM test and improvement percentage. Finally, empirical results demonstrate that the proposed hybrid model outperforms other models.

Yellow corn wholesale price forecasts via the neural network

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“…, 2015; Yoosefzadeh-Najafabadi et al. , 2021; Zhang et al. , 2021; Zhao, 2021), decision tree (Abreham, 2019; Degife & Sinamo, 2019; Dias & Rocha, 2019; Harris, 2017; Lopes, 2018; Surjandari et al.…”

MeDERT: A Metal Surface Defect Detection Model

“…The proposed MeDERT model becomes the SOTA model for the above three datasets. In recent years, most of the methods mentioned in other similar research literature have the disadvantages of not being able to process more complex images and the long learning time required upfront through deep learning methods [13]- [16], while the new method mentioned in this study has the following advantages：…”

Canola and soybean oil price forecasts via neural networks

“…Recently, machine learning techniques have revealed their great potential for price and yield forecasts of a wide spectrum of agricultural commodities (Yuan et al 2020;Rl and Mishra 2021;Storm et al 2020;Kouadio et al 2018;Abreham 2019;Huy et al 2019;Degife and Sinamo 2019;Naveena et al 2017;Lopes 2018;Mayabi 2019;Moreno and Salazar 2018;Zelingher et al 2021;Shahhosseini et al 2021Shahhosseini et al , 2020dos Reis Filho 2020;Zelingher et al 2020;Ribeiro et al 2019;Surjandari et al 2015;Ayankoya et al 2016;Ali et al 2018;Fang et al 2020;Harris 2017;Li et al 2020a;Yoosefzadeh-Najafabadi et al 2021;Ribeiro and dos Santos 2020;Zhao 2021;Jiang et al 2019;Handoyo and Chen 2020;Silalahi 2013;Li et al 2020b;Ribeiro and Oliveira 2011;Zhang et al 2021;Melo et al 2007;de Melo et al 2004;Kohzadi et al 1996;Zou et al 2007;Rasheed et al 2021;Khamis and Abdullah 2014;Dias (Vajda and Santosh 2016;Elliott et al 2020). For example, a fast method has been p...…”

“…and Rocha 2019; Gómez et al 2021;Silva et al 2019;Deina et al 2011;Filippi et al 2019;Wen et al 2021), such as soybeans (dos Reis Filho 2020; Li et al 2020a;Yoosefzadeh-Najafabadi et al 2021;Ribeiro and dos Santos 2020;Zhao 2021;Jiang et al 2019;Handoyo and Chen 2020), soybean oil (Silalahi 2013;Li et al 2020b), sugar (Surjandari et al 2015;Ribeiro and Oliveira 2011;Zhang et al 2021;Melo et al 2007;de Melo et al 2004;Silva et al 2019), corn (Xu and Zhang 2021f;Mayabi 2019;Moreno and Salazar 2018;Zelingher et al 2021;Shahhosseini et al 2021Shahhosseini et al , 2020dos Reis Filho 2020;Zelingher et al 2020;Ribeiro et al 2019;Surjandari et al 2015;Ayankoya et al 2016), wheat (Fang et al 2020;Ribeiro and dos Santos 2020;Kohzadi et al 1996;Zou et al 2007;Rasheed et al 2021;Khamis and Abdullah 2014;Dias and Rocha 2019;Gómez et al 2021), coffee (Kouadio et al 2018;…”