Title :
Extended Kalman Filter (EKF) prediction of flood water level
Author :
Adnan, Ramli ; Ruslan, Fazlina Ahmat ; Samad, Abd Manan ; Zain, Zainazlan Md
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
Abstract :
This paper addresses Extended Kalman Filter (EKF) algorithm that is uses to predict and estimate flood water level. In this respect, good estimates of the flood water level are needed to enable the filter to generate accurate forecasts. The EKF is the best predictor of the flood water level as it is the extended of the basic Kalman Filter algorithm that is only able to solve linear problems. EKF is developed to solve nonlinear problems and flood phenomenon suite well as the water level fluctuates highly nonlinear. This theory is also supported with the simulation results that produce small value of Root Mean Square Error (RMSE) which is close to zero.
Keywords :
Kalman filters; floods; forecasting theory; level measurement; prediction theory; EKF prediction; RMSE; extended Kalman filter; flood phenomenon; flood water level estimation; forecasts; nonlinear problems; root mean square error; Equations; Floods; Jacobian matrices; Kalman filters; Mathematical model; Prediction algorithms; Time measurement; Extended Kalman Filter (EKF); Kalman Filter; Tracking and Prediction;
Conference_Titel :
Control and System Graduate Research Colloquium (ICSGRC), 2012 IEEE
Conference_Location :
Shah Alam, Selangor
Print_ISBN :
978-1-4673-2035-1
DOI :
10.1109/ICSGRC.2012.6287156
