References
- Adeli, H., Ghosh-Dastidar, S., & Dadmehr, N. (2007). A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy. IEEE Transactions on Bio-Medical Engineering, 54(2), 205–211. https://doi.org/10.1109/TBME.2006.886855
- Ardito, R., & Cocchetti, G. (2006). Statistical approach to damage diagnosis of concrete dams by radar monitoring: Formulation and a pseudo-experimental test. Engineering Structures, 28(14), 2036–2045. https://doi.org/10.1016/j.engstruct.2006.04.001
- Ardito, R., Maier, G., & Massalongo, G. (2008). Diagnostic analysis of concrete dams based on seasonal hydrostatic loading. Engineering Structures, 30(11), 3176–3185. https://doi.org/10.1016/j.engstruct.2008.04.008
- Casciati, F., & Casciati, S. (2006). Structural health monitoring by Lyapunov exponents of non‐linear time series. Structural Control and Health Monitoring, 13(1), 132–146. https://doi.org/10.1002/stc.141
- Dai, B., Gu, C., Zhao, E., & Qin, X. (2018). Statistical model optimized random forest regression model for concrete dam deformation monitoring. Structural Control and Health Monitoring, 25(6), e2170. https://doi.org/10.1002/stc.2170
- Faes, L., Kugiumtzis, D., Nollo, G., Jurysta, F., & Marinazzo, D. (2015). Estimating the decomposition of predictive information in multivariate systems. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 91(3), 032904. https://doi.org/10.1103/PhysRevE.91.032904
- Faes, L., Nollo, G., & Porta, A. (2011). Information-based detection of nonlinear Granger causality in multivariate processes via a nonuniform embedding technique. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 83(5 Pt 1), 051112. https://doi.org/10.1103/PhysRevE.83.051112
- Gençağa, D. (2018). Transfer entropy. Entropy, 20(4), 288. https://doi.org/10.3390/e20040288
- Gu, C., Li, Z., & Xu, B. (2011). Abnormality diagnosis of cracks in the concrete dam based on dynamical structure mutation. Science China Technological Sciences, 54(7), 1930–1939. https://doi.org/10.1007/s11431-011-4331-2
- Gu, C., & Wu, Z. (2006). Safety monitoring of dams and dam foundations-theories & methods and their application. Hohai University Press. (in Chinese)
- Gu, C., Zhao, E., Jin, Y., & Su, H. (2011). Singular value diagnosis in dam safety monitoring effect values. Science China Technological Sciences, 54(5), 1169–1176. https://doi.org/10.1007/s11431-011-4339-7
- Hu, J., & Ma, F. (2021). Comparison of hierarchical clustering based deformation prediction models for high arch dams during the initial operation period. Journal of Civil Structural Health Monitoring, 11(4), 897–914. https://doi.org/10.1007/s13349-021-00487-8
- Hung, Y. C., & Hu, C. K. (2008). Chaotic communication via temporal transfer entropy. Physical Review Letters, 101(24), 244102. https://doi.org/10.1103/PhysRevLett.101.244102
- Hu, J., & Wu, S. (2019). Statistical modeling for deformation analysis of concrete arch dams with influential horizontal cracks. Structural Health Monitoring, 18(2), 546–562. https://doi.org/10.1177/1475921718760309
- ICOLD. (2005). Risk assessment in dam safety management: A reconnaissance of benefits, methods and current applications. Bulletin 130. ICOLD
- Kim, H. S., Eykholt, R., & Salas, J. D. (1999). Nonlinear dynamics, delay times, and embedding windows. Physica D: Nonlinear Phenomena, 127(1-2), 48–60. https://doi.org/10.1016/S0167-2789(98)00240-1
- Liu, H., Zhang, Q., Gu, C., Su, H., & Li, V. (2017). Influence of microcrack self-healing behavior on the permeability of Engineered Cementitious Composites. Cement and Concrete Composites, 82, 14–22. https://doi.org/10.1016/j.cemconcomp.2017.04.004
- Mallat, S. G. (1999). A wavelet tour of signal processing. Academic Press.
- Mao, X., & Shang, P. (2017). Transfer entropy between multivariate time series. Communications in Nonlinear Science and Numerical Simulation, 47, 338–347. https://doi.org/10.1016/j.cnsns.2016.12.008
- Mata, J., Tavares de Castro, A., & Sá da Costa, J. (2014). Constructing statistical models for arch dam deformation. Structural Control and Health Monitoring, 21(3), 423–437. https://doi.org/10.1002/stc.1575
- Montalto, A., Faes, L., & Marinazzo, D. (2014). MuTE: A MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy. PloS One, 9(10), e109462. https://doi.org/10.1371/journal.pone.0109462
- Nichols, J., Bucholtz, F., & Michalowicz, J. (2013). Linearized transfer entropy for continuous second order systems. Entropy, 15(12), 3186–3204. https://doi.org/10.3390/e15083276
- Nichols, J. M., Seaver, M., Trickey, S. T., Todd, M. D., Olson, C., & Overbey, L. (2005). Detecting nonlinearity in structural systems using the transfer entropy. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 72(4 Pt 2), 046217. https://doi.org/10.1103/PhysRevE.72.046217
- Nichols, J. M., Todd, M. D., Seaver, M., & Virgin, L. N. (2003a). Use of chaotic excitation and attractor property analysis in structural health monitoring. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 67(1 Pt 2), 016209. https://doi.org/10.1103/PhysRevE.67.016209
- Nichols, J. M., Virgin, L. N., Todd, M. D., & Nichols, J. D. (2003b). On the use of attractor dimension as a feature in structural health monitoring. Mechanical Systems and Signal Processing, 17(6), 1305–1320. https://doi.org/10.1006/mssp.2002.1521
- Nourani, V., Alami, M. T., & Vousoughi, F. D. (2015). Wavelet-entropy data pre-processing approach for ANN-based groundwater level modeling. Journal of Hydrology, 524, 255–269. https://doi.org/10.1016/j.jhydrol.2015.02.048
- Overbey, L. A., & Todd, M. D. (2009a). Dynamic system change detection using a modification of the transfer entropy. Journal of Sound and Vibration, 322(1-2), 438–453. https://doi.org/10.1016/j.jsv.2008.11.025
- Overbey, L. A., & Todd, M. D. (2009b). Effects of noise on transfer entropy estimation for damage detection. Mechanical Systems and Signal Processing, 23(7), 2178–2191. https://doi.org/10.1016/j.ymssp.2009.03.016
- Peyras, L., Royet, P., & Boissier, D. (2006). Dam ageing diagnosis and risk analysis: Development of methods to support expert judgment. Canadian Geotechnical Journal, 43(2), 169–186. https://doi.org/10.1139/t05-096
- Quek, S.-T., Wang, Q., Zhang, L., & Ang, K.-K. (2001). Sensitivity analysis of crack detection in beams by wavelet technique. International Journal of Mechanical Sciences, 43(12), 2899–2910. https://doi.org/10.1016/S0020-7403(01)00064-9
- Rogers, J. D., & McMahon, D. J. (1992). Reassessment of the St. Francis dam failure. Rogers/Pacific, Incorporated.
- Rosenstein, M. T., Collins, J. J., & De Luca, C. J. (1993). A practical method for calculating largest Lyapunov exponents from small data sets. Physica D: Nonlinear Phenomena, 65(1–2), 117–134. https://doi.org/10.1016/0167-2789(93)90009-P
- Salazar, F., Morán, R., Toledo, M. Á., & Oñate, E. (2017). Data-based models for the prediction of dam behaviour: A review and some methodological considerations. Archives of Computational Methods in Engineering, 24(1), 1–21. https://doi.org/10.1007/s11831-015-9157-9
- Schreiber, T. (2000). Measuring information transfer. Physical Review Letters, 85(2), 461–464. https://doi.org/10.1103/PhysRevLett.85.461
- Serafim, J. L. (1987). Malpasset dam discussion—remembrances of failures of dams. Engineering Geology, 24(1-4), 355–366.
- Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
- Su, H., Hu, J., & Wu, Z. (2012). A study of safety evaluation and early-warning method for dam global behavior. Structural Health Monitoring, 11(3), 269–279.
- Sun, W., & Yan, D. (2014). Identification of the nonlinear vibration characteristics in hydropower house using transfer entropy. Nonlinear Dynamics, 75(4), 673–691. https://doi.org/10.1007/s11071-013-1094-2
- Su, H., Wen, Z., Chen, Z., & Tian, S. (2016). Dam safety prediction model considering chaotic characteristics in prototype monitoring data series. Structural Health Monitoring, 15(6), 639–649. https://doi.org/10.1177/1475921716654963
- Wang, S., Xu, C., Liu, Y., & Wu, B. (2022). A spatial association-coupled double objective support vector machine prediction model for diagnosing the deformation behaviour of high arch dams. Structural Health Monitoring, 21(3), 945–964. https://doi.org/10.1177/14759217211017030
- Wu, Z. (2003). Safety monitoring theory and its application of hydraulic structures. Higher Education.
- Zhao, E., & Wu, C. (2021). Risk probabilistic assessment of ultrahigh arch dams through regression panel modeling on deformation behavior. Structural Control and Health Monitoring, 28(5), e2716. https://doi.org/10.1002/stc.2716