An Integrated Approach to Forecasting Intermittent Demand for Electric Power Materials-Reference-Cited by-同舟云学术

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An Integrated Approach to Forecasting Intermittent Demand for Electric Power Materials

Published:2018-03-07 Issue:4 Volume:53 Page:1309-1335
ISSN:0927-7099
Container-title:Computational Economics
language:en
Short-container-title:Comput Econ

Author:

Jiang Aiping,Chi Qiuguo,Gao Junjun,Wu Maoguo

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s10614-018-9805-x.pdf

Reference28 articles.

1. Al-Ghamdi, A. S. (2002). Using logistic regression to estimate the influence of accident factors on accident severity. Accident Analysis & Prevention, 34(6), 729–741.

2. Croston, J. D. (1972). Forecasting and stock control for intermittent demands. Operational Research Quarterly (1970–1977), 23(3), 289–303. https://doi.org/10.2307/3007885 .

3. Dolgui, A., & Pashkevich, M. (2008). Demand forecasting for multiple slow-moving items with short requests history and unequal demand variance. International Journal of Production Economics, 112(2), 885–894.

4. Hua, Z., & Zhang, B. (2006). A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts. Applied Mathematics and Computation, 181(2), 1035–1048.

5. Hua, Z. S., Zhang, B., Yang, J., & Tan, D. S. (2007). A new approach of forecasting intermittent demand for spare parts inventories in the process industries. Journal of the Operational Research Society, 58(1), 52–61.

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