Volume 3, Issue 3, September 2010, Pages 266 - 273
Reliability Growth Predication based on an Improved Grey Predicton Model
Yuhong Wang, Yaoguo Dang, Sifeng Liu
Available Online 1 September 2010.
- https://doi.org/10.2991/ijcis.2010.3.3.2How to use a DOI?
- reliability growth, GM(1,1) model, the initial condition, first-order accumulated generation operator.
- As limits of time, labors and expenses, observed data usually have the characteristic of small sample sizes in development test program. Redesigns or corrective actions can result in changes of reliability for equipments. We propose an improved GM(1,1) model to predict reliability growth in this paper. First, a newly initial condition in time response function is set in this improved GM(1,1) model. The newly initial condition is comprised of the first item and the last item of a sequence which is generated from applying the first-order accumulated generation operator to a sequence of raw data. Then the improved model can express the principle of new information priority well and improve prediction precision through fully applying new information in raw data. Secondly, we make use of the improved model to predict reliability growth in a numerical example. The comparison of predicted reliability growth curve from the improved GM(1,1) model and that from the Lloyd-Lipow model indicates that the improved GM(1,1) model is much better than the Lloyd-Lipow model for the reliability growth prediction.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Yuhong Wang AU - Yaoguo Dang AU - Sifeng Liu PY - 2010 DA - 2010/09 TI - Reliability Growth Predication based on an Improved Grey Predicton Model JO - International Journal of Computational Intelligence Systems SP - 266 EP - 273 VL - 3 IS - 3 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2010.3.3.2 DO - https://doi.org/10.2991/ijcis.2010.3.3.2 ID - Wang2010 ER -