Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2016, Article ID 1656738, 11 pages
http://dx.doi.org/10.1155/2016/1656738
Research Article

Seepage Monitoring Models Study of Earth-Rock Dams Influenced by Rainstorms

Jianchun Qiu,1,2,3 Dongjian Zheng,1,2,3 and Kai Zhu2,3

1State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
2National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
3College of Water-Conservancy and Hydropower, Hohai University, Nanjing 210098, China

Received 20 November 2015; Revised 2 March 2016; Accepted 10 March 2016

Academic Editor: Sajid Hussain

Copyright © 2016 Jianchun Qiu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Li and F. Wang, Design and Construction of Earth Rock Dam, China Waterpower Press, Beijing, China, 2011.
  2. T. V. Panthulu, C. Krishnaiah, and J. M. Shirke, “Detection of seepage paths in earth dams using self-potential and electrical resistivity methods,” Engineering Geology, vol. 59, no. 3-4, pp. 281–295, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Lamea and H. Mirzabozorg, “Simulating nonlinear behavior of AAR-affected arch dams including detection of crack profiles,” Arabian Journal for Science and Engineering, vol. 40, no. 2, pp. 329–341, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. C.-H. Wu, S.-C. Chen, and Z.-Y. Feng, “Formation, failure, and consequences of the Xiaolin landslide dam, triggered by extreme rainfall from Typhoon Morakot, Taiwan,” Landslides, vol. 11, no. 3, pp. 357–367, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. Z. Wu, Safety Monitoring Theory and Its Application of Hydraulic Structures, Higher Education Press, Beijing, China, 2003.
  6. H. Huang and B. Chen, “Dam seepage monitoring model based on dynamic effect weight of reservoir water level,” Energy Procedia, vol. 16, pp. 159–165, 2012. View at Publisher · View at Google Scholar
  7. B. J. Li and C. T. Cheng, “Monthly discharge forecasting using wavelet neural networks with extreme learning machine,” Science China Technological Sciences, vol. 57, no. 12, pp. 2441–2452, 2014. View at Publisher · View at Google Scholar · View at Scopus
  8. H. Loussifi, K. Nouri, and N. B. Braiek, “A new efficient hybrid intelligent method for nonlinear dynamical systems identification: the Wavelet Kernel Fuzzy Neural Network,” Communications in Nonlinear Science & Numerical Simulation, vol. 32, pp. 10–30, 2016. View at Publisher · View at Google Scholar · View at Scopus
  9. B. Doucoure, K. Agbossou, and A. Cardenas, “Time series prediction using artificial wavelet neural network and multi-resolution analysis: application to wind speed data,” Renewable Energy, vol. 92, pp. 202–211, 2016. View at Publisher · View at Google Scholar
  10. H. Gzyl, E. ter Horst, and G. Molina, “Application of the method of maximum entropy in the mean to classification problems,” Physica A, vol. 437, Article ID 16220, pp. 101–108, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. H. Cui and V. P. Singh, “Maximum entropy spectral analysis for streamflow forecasting,” Physica A: Statistical Mechanics and Its Applications, vol. 442, pp. 91–99, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. F. A. N. Palmieri and D. Ciuonzo, “Objective priors from maximum entropy in data classification,” Information Fusion, vol. 14, no. 2, pp. 186–198, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. A. SaiToh, R. Rahimi, and M. Nakahara, “A quantum genetic algorithm with quantum crossover and mutation operations,” Quantum Information Processing, vol. 13, no. 3, pp. 737–755, 2014. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  14. H.-L. Liu, “Acoustic partial discharge localization methodology in power transformers employing the quantum genetic algorithm,” Applied Acoustics, vol. 102, pp. 71–78, 2016. View at Publisher · View at Google Scholar · View at Scopus
  15. E. Pomponi, A. Vinogradov, and A. Danyuk, “Wavelet based approach to signal activity detection and phase picking: application to acoustic emission,” Signal Processing, vol. 115, pp. 110–119, 2015. View at Publisher · View at Google Scholar · View at Scopus
  16. A. Alhasan, D. J. White, and K. De Brabanterb, “Continuous wavelet analysis of pavement profiles,” Automation in Construction, vol. 63, pp. 134–143, 2016. View at Publisher · View at Google Scholar
  17. M. A. Goulart, L. Sanches, M. T. Vilani, and O. B. P. Júnior, “Analysis of evapotranspiration by Morlet wavelet in area of Vochysia divergens Pohl in Pantanal,” Revista Brasileira de Engenharia Agricola e Ambiental, vol. 19, no. 2, pp. 93–98, 2015. View at Publisher · View at Google Scholar · View at Scopus