Detect and Correct Abnormal Values in Uncertain Environment: Application to Demand Forecast - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Detect and Correct Abnormal Values in Uncertain Environment: Application to Demand Forecast

Abstract

This article presents the first results of a study which deals with the detection and the correction of abnormal values in data series intended to forecast demand. This work fits in the broader context of performance management for proximity retailers. Indeed, when this kind of point of sales (POS) is studied, sales volumes are often too small to be effectively exploited by statistical processing methods. It is therefore useful to consolidate the information with expertise and additional knowledge resulting from similar POS. It is also relevant to take into account the inherent uncertainty of such information. The proposal of this paper is a methodological contribution which uses consolidated knowledge to detect and correct abnormal values and to improve the quality of data used to implement forecast methods.
Fichier principal
Vignette du fichier
978-3-662-44739-0_9_Chapter.pdf (675.3 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01388209 , version 1 (26-10-2016)

Licence

Attribution

Identifiers

Cite

Eric Villeneuve, Cédrick Béler, Laurent Geneste. Detect and Correct Abnormal Values in Uncertain Environment: Application to Demand Forecast. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2014, Ajaccio, France. pp.67-75, ⟨10.1007/978-3-662-44739-0_9⟩. ⟨hal-01388209⟩
79 View
86 Download

Altmetric

Share

Gmail Facebook X LinkedIn More