Title of article :
Cavitation Damage Prediction on Dam Spillways using Fuzzy-KNN Modeling
Author/Authors :
Fadaei Kermani, E Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran , Barani, G. A Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran , Ghaeini Hessaroeyeh, M Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran
Abstract :
The present paper deals with a numerical method for prediction of cavitation damage level and location on
dam spillways. A method was applied to predict the intensity of cavitation damage to spillways, using the
fuzzy k-nearest neighbor algorithm. Five levels of damage intensity were considered to predict cavitation
damage in the spillway of Karun-1 Dam in Iran. According to the results, the proposed model could properly
predict the location and intensity of damage in comparison with the actual damage reports of past floods.
According to the Pearson's correlation coefficient, mean absolute error, coefficient of residual mass, and
normalized root mean square error, the fuzzy k-nearest neighbor model is efficient and suitable.
Keywords :
Damage intensity , Fuzzy k-nearest neighbor model , Cavitation damage , Spillways
Journal title :
Astroparticle Physics