Estimation of Streamflow Using Takagi-Sugeno Fuzzy Rule-Based Model

In this study, a tool is developed to estimate streamflow at Guvenc Basin, Ankara by using Takagi-Sugeno (TS) Fuzzy Rule-Based (RB) model. The model takes precipitation and runoff at time � as predictor (input) and estimates the runoff at time � + 1. The approach used to generate the TS RB model is based on density based clustering. Each cluster center is used to generate a fuzzy rule that represents the system behaviour. Satisfactory results are obtained especially after including the seasonal behaviour of streamflow time series into the model.


Estimation of the Hurst parameter for fractional Brownian motion using the CMARS method
Yerlikaya-Ozkurt, F.; Vardar Acar, Ceren; Yolcu-Okur, Y.; Weber, G. -W. (2014-03-15)
In this study, we develop an alternative method for estimating the Hurst parameter using the conic multivariate adaptive regression splines (CMARS) method. We concentrate on the strong solutions of stochastic differential equations (SDEs) driven by fractional Brownian motion (fBm). Our approach is superior to others in that it not only estimates the Hurst parameter but also finds spline parameters of the stochastic process in an adaptive way. We examine the performance of our estimations using simulated tes...
Estimation of hydrologic parameters of Kocanaz watershed by a hydrologic model
Akay, Hüseyin; Baduna Koçyiğit, Müsteyde; Yanmaz, Ali Melih (2017-01-01)
The main goal of this study is to estimate the hydrologic parameters of Kocanaz watershed located in Western Black Sea Region, using a semi-distributed hydrologic model, Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). In this study, the hydrologic model was set up for two flood events occurred in 2002 and 2013, in which one was used for calibration while the other one was used for validation of the calibrated hydrologic parameters. The watershed was introduced into the model as a sing...
Implementation of different algorithms in linear mixed models: case studies with TIMSS
Koca, Burcu; Gökalp Yavuz, Fulya; Department of Statistics (2021-9-06)
Mixed models are frequently used in longitudinal data types with time repetition over the same subject and clustered data types formed by observations gathered around certain groups. The modeling technique which models the dependency structure between repetitions and observations in the same cluster is required to use algorithms for parameter estimations. The same model can be solved with various algorithms arising from setup, inference and approach differences. In this study, several algorithms used for LM...
Estimation of pico-satellite attitude dynamics and external torques via Unscented Kalman Filter
Söken, Halil Ersin (FapUNIFESP (SciELO), 2014-01-01)
In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The sa...
Analysis of Model Variance for Ensemble Based Turbulence Modeling
Jiang, Nan; Kaya Merdan, Songül; Layton, William (Walter de Gruyter GmbH, 2015-04-01)
This report develops an ensemble or statistical eddy viscosity model. The model is parameterized by an ensemble of solutions of an ensemble-Leray regularization. The combined approach of ensemble time stepping and ensemble eddy viscosity modeling allows direct parametrization of the turbulent viscosity co-efficient. We prove unconditional stability and that the model's solution approaches statistical equilibrium as t -> infinity; the model's variance converges to zero as t -> infinity. The ensemble method i...
Citation Formats
Ö. B. Akgün and E. Kentel Erdoğan, “Estimation of Streamflow Using Takagi-Sugeno Fuzzy Rule-Based Model,” 2018, Accessed: 00, 2020. [Online]. Available: