Improving sporadic demand forecasting using a modified k-nearest neighbor framework-Reference-Cited by-同舟云学术

Improving sporadic demand forecasting using a modified k-nearest neighbor framework

Published:2024-03 Issue: Volume:129 Page:107633
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Hasan Nazmul^ORCID,Ahmed Nafi^ORCID,Ali Syed Mithun^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference43 articles.

1. Forecasting spare parts sporadic demand using traditional methods and machine learning—a comparative study;Adur Kannan;SMU Data Science Review,2020

2. Forecasting supply chain sporadic demand using support vector machine approaches;Ahmed;Fuzzy Set Syst.,2020

3. Effects of correlation on intermittent demand forecasting and stock control;Altay;Int. J. Prod. Econ.,2012

4. Application Of Artificial Intelligence in Forecasting: A Systematic Review (SSRN Scholarly Paper 3483313);Annor Antwi,2019

5. A new method to forecast intermittent demand in the presence of inventory obsolescence;Babai;Int. J. Prod. Econ.,2019

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