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

fYear

2012

fDate

16-17 July 2012

Firstpage

171

Lastpage

174

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and System Graduate Research Colloquium (ICSGRC), 2012 IEEE

Conference_Location

Shah Alam, Selangor

Print_ISBN

978-1-4673-2035-1

Type

conf

DOI

10.1109/ICSGRC.2012.6287156

Filename

6287156