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 Style AAA Style APA 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, September 12). Spare Parts Prediction: A Comparative Analysis of Croston and its variations, Willemain, Machine Learning, Hybrid, and Combined Methods. Business Economics. Retrieved from http://hdl.handle.net/2105/66740

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