Fatigue Life Prognosis of Concrete Using Extended Grey Markov Model and PSOA
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| Title | Fatigue Life Prognosis of Concrete Using Extended Grey Markov Model and PSOA |
| Authors | |
| Abstract | The fatigue life prognosis of concrete is becoming more important with the development for demanding higher quality and safety in industrial. However, effective methods for this prognosis are still in need now, due to the feature of concrete. This paper proposes the extended grey Markov model (i.e. EGMM) for fatigue life prognosis of concrete. Firstly, the GM (1, 1, λ1, λ2) (i.e. EGM) is proposed by integrating the particle swarm optimization algorithm (PSOA) with GM (1, 1) (i.e. GM). Then the Markov model is integrated with EGM and a novel prognosis method of the extended grey Markov model is proposed. In the proposed method, the PSOA is used to optimize the parameters of EGM so that EGM can obtain better health states of concrete. The extended grey Markov model is used to combine the health states and transition probability, and obtain better and more accurate fatigue life of concrete. And a real case study is used to demonstrate the implementation and potential applications of the proposed fatigue life prognosis approach on concrete. |
| Publisher | World Science Publisher |
| Date | 2012-03-16 |
| Source | 2167-6348 |
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