22 citations as recorded by crossref.

1. Nonlinear analysis of rainfall variability in Australia B. Sivakumar et al. https://doi.org/10.1007/s00477-013-0689-y
2. Modelling and control of chaotic processes through their Bifurcation Diagrams generated with the help of Recurrent Neural Network models: Part 1—simulation studies J. Krishnaiah et al. https://doi.org/10.1016/j.jprocont.2005.04.002
3. Meteorological complexity in the Amazonian area of Ecuador: An approach based on dynamical system theory H. Millán et al. https://doi.org/10.1016/j.ecocom.2009.05.004
4. Chaos theory in geophysics: past, present and future B. Sivakumar https://doi.org/10.1016/S0960-0779(03)00055-9
5. Variability of flow discharge in lateral inflow-dominated stream channels C. Chang & H. Yeh https://doi.org/10.5194/hess-19-2505-2015
6. Streamflow variability and classification using false nearest neighbor method R. Vignesh et al. https://doi.org/10.1016/j.jhydrol.2015.10.056
7. Nonlinear Dynamic Modeling of Urban Water Consumption Using Chaotic Approach (Case Study: City of Kelowna) P. Yousefi et al. https://doi.org/10.3390/w12030753
8. Consequences of Continuous Zero Values and Constant Values in Time Series Modeling: Understanding through Chaotic Approach T. Fathima & V. Jothiprakash https://doi.org/10.1061/(ASCE)HE.1943-5584.0001367
9. Characterizing cross-scale chaotic behaviors of the runoff time series in an inland river of Central Asia Z. Hu et al. https://doi.org/10.1016/j.quaint.2013.07.031
10. On the nonlinear interaction between global teleconnection patterns V. Khokhlov et al. https://doi.org/10.1256/qj.05.05
11. River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches B. Sivakumar et al. https://doi.org/10.1016/S0022-1694(02)00112-9
12. Investigating Chaos and Nonlinear Forecasting in Short Term and Mid-term River Discharge M. Zounemat-Kermani https://doi.org/10.1007/s11269-016-1258-1
13. Mid- and long-term runoff predictions by an improved phase-space reconstruction model M. Hong et al. https://doi.org/10.1016/j.envres.2015.11.024
14. A phase-space reconstruction approach to prediction of suspended sediment concentration in rivers B. Sivakumar https://doi.org/10.1016/S0022-1694(01)00573-X
15. The Concept of Rainwater Management in Area of Košice Region M. Zeleňáková & G. Hudáková https://doi.org/10.1016/j.proeng.2014.11.448
16. Chaotic analysis of daily rainfall series in Koyna reservoir catchment area, India V. Jothiprakash & T. Fathima https://doi.org/10.1007/s00477-012-0673-y
17. Nonlinear determinism in river flow: prediction as a possible indicator B. Sivakumar https://doi.org/10.1002/esp.1462
18. Chaotic Analysis of Reservoir Inflow Series: A Case Study on Koyna Reservoir Inflow V. Jothiprakash & T. Fathima https://doi.org/10.1007/s40030-013-0047-6
19. A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework Z. Liang et al. https://doi.org/10.1007/s00704-017-2186-6
20. SOFT COMPUTING TOOLS IN RAINFALL-RUNOFF MODELING V. Jothiprakash & R. Magar https://doi.org/10.1080/09715010.2009.10514970
21. Chaos theory applied to the modelling of karst springs: first results from univariate time series S. Mangiarotti et al. https://doi.org/10.1007/s10040-019-01971-8
22. Sediment transport phenomenon in rivers: an alternative perspective B. Sivakumar & A. Jayawardena https://doi.org/10.1016/S1364-8152(03)00083-5