Spare Parts Prediction: A Comparative Analysis of Croston and its variations, Willemain, Machine Learning, Hybrid, and Combined Methods

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Keywords	Spare Parts Demand Forecasting; Intermittency; Croston; Ensemble Methods; Stacking Methods; Simulated and Industrial Data Sets; Accuracy Performance ; Inventory Performance ; Data Aggregation; Hybrid Method; Machine Learning Methods
Thesis Advisor	Dekker, R
Persistent URL	hdl.handle.net/2105/66740
Series	Business Economics
Organisation	Erasmus School of Economics
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Chen, T. (2023). Spare Parts Prediction: A Comparative Analysis of Croston and its variations, Willemain, Machine Learning, Hybrid, and Combined Methods. In Business Economics.http://hdl.handle.net/2105/66740

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