Version 1
: Received: 24 August 2017 / Approved: 25 August 2017 / Online: 25 August 2017 (08:21:40 CEST)
How to cite:
Boiko, T.; Karpenkov, O.; Rakhimberdiev, B. Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints2017, 2017080086. https://doi.org/10.20944/preprints201708.0086.v1
Boiko, T.; Karpenkov, O.; Rakhimberdiev, B. Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints 2017, 2017080086. https://doi.org/10.20944/preprints201708.0086.v1
Boiko, T.; Karpenkov, O.; Rakhimberdiev, B. Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints2017, 2017080086. https://doi.org/10.20944/preprints201708.0086.v1
APA Style
Boiko, T., Karpenkov, O., & Rakhimberdiev, B. (2017). Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints. https://doi.org/10.20944/preprints201708.0086.v1
Chicago/Turabian Style
Boiko, T., Oleg Karpenkov and Bulat Rakhimberdiev. 2017 "Forecasting Algorithms for Recurrent Patterns in Consumer Demand" Preprints. https://doi.org/10.20944/preprints201708.0086.v1
Abstract
In this paper we develop a forecasting algorithm for recurrent patterns in consumer demand. We study this problem in two different settings: pull and push models. We discuss several features of the algorithm concerning sampling, periodic approximation, denoising and forecasting.
Keywords
seasonality; forecasting; pull and push models; denoising
Subject
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
