Research laboratory in Industrial Safety Engineering and Sustainable Development

Institute of Maintenance and Industrial Safety


Curriculum vitae


University of Oran2 Mohamed ben Ahmed



Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: An artificial neural network approach


Journal article


Khaled Ziane, Soraya Zebirate, Adel Zaitri
Wind Engineering, vol. 40, 2016 Jun, pp. 189--198


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Cite

APA   Click to copy
Ziane, K., Zebirate, S., & Zaitri, A. (2016). Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: {An} artificial neural network approach. Wind Engineering, 40, 189–198. https://doi.org/10.1177/0309524X16641849


Chicago/Turabian   Click to copy
Ziane, Khaled, Soraya Zebirate, and Adel Zaitri. “Fatigue Strength Prediction in Composite Materials of Wind Turbine Blades under Dry–Wet Conditions: {An} Artificial Neural Network Approach.” Wind Engineering 40 (June 2016): 189–198.


MLA   Click to copy
Ziane, Khaled, et al. “Fatigue Strength Prediction in Composite Materials of Wind Turbine Blades under Dry–Wet Conditions: {An} Artificial Neural Network Approach.” Wind Engineering, vol. 40, June 2016, pp. 189–98, doi:10.1177/0309524X16641849.


BibTeX   Click to copy

@article{ziane2016a,
  title = {Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: {An} artificial neural network approach},
  year = {2016},
  month = jun,
  journal = {Wind Engineering},
  pages = {189--198},
  volume = {40},
  doi = {10.1177/0309524X16641849},
  author = {Ziane, Khaled and Zebirate, Soraya and Zaitri, Adel},
  month_numeric = {6}
}


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