Affiliated with RCfalse
LSTM with particle Swam optimization for sales forecasting
He, Qi Qiao; Wu, Cuiyu; Si, Yain Whar
Source PublicationElectronic Commerce Research and Applications
ABS Journal Level2

Sales volume forecasting is of great significance to E-commerce companies. Accurate sales forecasting enables managers to make reasonable resource allocation in advance. In this paper, we propose a novel approach based on Long Short-Term Memory with Particle Swam Optimization (LSTM-PSO) for sale forecasting in E-commerce companies. In the proposed approach, the number of hidden neurons in different LSTM layers, and the number of iterations for training are optimized by Particle Swam Optimization metaheuristic. In the experiments, we compare the proposed approach with 9 competing approaches. The effectiveness of the proposed approach is evaluated on the real datasets from an E-commerce company as well as on the publicly available benchmark datasets. In the experiments, neural network design, activation functions, methods of regularization, and the training method of neural network are also analyzed. Experiment results show that the proposed PSO-LSTM models achieved good results in forecasting accuracy.

KeywordE-commerce Long Short-term Memory Particle Swam Optimization Sales Forecasting Time Series
URLView the original
Indexed BySCIE ; SSCI
WOS Research AreaBusiness & Economics ; Computer Science
WOS SubjectBusiness ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000746062400007
Scopus ID2-s2.0-85122631499
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorHe, Qi Qiao
AffiliationDepartment of Computer and Information Science, University of Macau, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
He, Qi Qiao,Wu, Cuiyu,Si, Yain Whar. LSTM with particle Swam optimization for sales forecasting[J]. Electronic Commerce Research and Applications,2022,51.
APA He, Qi Qiao,Wu, Cuiyu,&Si, Yain Whar.(2022).LSTM with particle Swam optimization for sales forecasting.Electronic Commerce Research and Applications,51.
MLA He, Qi Qiao,et al."LSTM with particle Swam optimization for sales forecasting".Electronic Commerce Research and Applications 51(2022).
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