Conferece: Anais do 15 Congresso Brasileiro de Inteligência Computacional

Artificial intelligence and signal decomposition approach applied to retail sales forecasting

Abstract

Sales forecasting is essential for decision-making and are crucial in many areas of a firm, such as planning and scheduling, resource management, marketing, logistics, and supply chain. Due to the fluctuations in retail sales, prediction with high accuracy is a challenging task. In this context, this study proposes a framework that combines ensemble empirical mode decomposition (EEMD) based on artificial intelligence models to forecast the retail sales of a Rossmann Store, using a multi-step-ahead forecasting strategy, in the task of time series forecasting with one, seven, and fourteen-days-ahead. The forecasting models of the retail sales time series are Bayesian Regularization of Artificial Neural Networks, Cubist Regression, and Support Vector Regression. The performance of the proposed forecasting models were evaluated by using two performance metrics: mean absolute percentage error and root mean squared percentage error. The EEMD models outperform the single models in all forecasting horizons, with a performance improvement that ranges 1.30% - 76.25%. Indeed, EEMD models are efficient and accurate models for retail sales forecasting.

DOI Slides

NoteHow to cite this work

Silva, Ramon Gomes da, Matheus Henrique Dal Molin Ribeiro, José Henrique Kleinübing Larcher, Viviana Cocco Mariani, and Leandro Santos Coelho. 2021. “Artificial Intelligence and Signal Decomposition Approach Applied to Retail Sales Forecasting.” In Anais Do 15 Congresso Brasileiro de Inteligência Computacional, edited by Carmelo Jos’e Albanez Bastos Filho, Hugo Valadares Siqueira, Danton Diego Ferreira, Douglas Wildgrube Bertol, and Roberto C’elio Limão de Oliveira. SBIC. https://doi.org/10.21528/CBIC2021-25.

@inproceedings{silva_artificial_2021,
 address = {Joinville, SC},
 author = {Silva, Ramon Gomes da and Ribeiro, Matheus Henrique Dal Molin and Larcher, José Henrique Kleinübing and Mariani, Viviana Cocco and Coelho, Leandro Santos},
 booktitle = {Anais do 15 Congresso Brasileiro de Inteligência Computacional},
 doi = {10.21528/CBIC2021-25},
 editor = {Filho, Carmelo Jos'e Albanez Bastos and Siqueira, Hugo Valadares and Ferreira, Danton Diego and Bertol, Douglas Wildgrube and Oliveira, Roberto C'elio Limão de},
 month = {October},
 pages = {1--6},
 publisher = {SBIC},
 title = {Artificial intelligence and signal decomposition approach applied to retail sales forecasting},
 year = {2021}
}