원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.9 No.8
2016.08
pp.277-286
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In order to improve the prediction accuracy of reverse returned logistics, considering it has the characteristics of high volatility and uncertainty, the paper used the theory of Markov Chain to modify the result of Grey prediction. And a Grey-Markov prediction model was established. Several parallel region has been divided used the prediction curve of Grey prediction model as symmetric center. And each region was a state interval. A practical example show that the average relative error rate and the variance ratio of Grey-Markov prediction model was smaller, and the prediction accuracy is higher comparing with the Grey prediction model. The model is effective and feasible.
목차
Abstract
1. Introduction
2. Mathematical Model
2.1. The Grey Prediction Model
2.2. The Markov Prediction Model
2.3. The Grey-Markov Prediction Model
3. Practical Example
4. Conclusion
References
1. Introduction
2. Mathematical Model
2.1. The Grey Prediction Model
2.2. The Markov Prediction Model
2.3. The Grey-Markov Prediction Model
3. Practical Example
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보