Discharge characteristics of a modified oblique side weir in subcritical flow

Borghei, Seyed Mehdi; Parvaneh, Ali

doi:10.1016/j.flowmeasinst.2011.04.009

Cited by 55 publications

(25 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The experimental dataset of Borghei and Parvaneh (2011) was used in this study. The main channel was of 11 and 0.4 m in length and width, respectively ( Fig.…”

Section: Experimental Datasetmentioning

confidence: 99%

“…The results of the investigation of the characteristics of the SVR models show that the optimum SVR model with the polynomial kernel function, using w=L; Fr 1 =sinh 0 ; w=Y 1 and wsinh 0 =Y 1 as input parameters, leads the most accurate model in predicting the discharge coefficient of a modified labyrinth side weir. In this part of the paper the results of Borghei and Parvaneh (2011) and Emiroglu et al (2010a) were compared with the SVR model. As mentioned before, in order to develop the SVR model, sixty percent of the whole dataset is considered as the training dataset and the rest forty percent is considered as the testing dataset.…”

Section: Determination Of the Best Input Combinationmentioning

confidence: 99%

“…In Fig. 4 the residuals of the SVR, Borghei and Parvaneh (2011) and Emiroglu et al (2010a) are shown by a filled line, filled squares and un-filled squares, respectively. According to this figure, the SVR residuals for the majority of the data are between -0.1 and 0.1, while those of Borghei and Parvaneh (2011) are between -0.3 and 0.3 and of the Emiroglu et al (2010a) between -1 and 0.7.…”

Section: Determination Of the Best Input Combinationmentioning

confidence: 99%

See 2 more Smart Citations

Optimum Support Vector Regression for Discharge Coefficient of Modified Side Weirs Prediction

Zaji

Bonakdari

2017

INAE Lett

View full text Add to dashboard Cite

Designing procedure of economical and safe side weirs that are used in various hydraulic structures such as intakes and deviation systems, essentially needs the ability to predict the side weirs' discharge capacity accurately. In this paper, the discharge coefficient of a modified labyrinth side weir was modeled by employing the support vector regression (SVR) method. To find the optimum SVR scenario, eight different kernel functions and six different input combinations were investigated. The accuracy of the SVR models were compared with two nonlinear regression equations from other published studies. The results showed that the SVR model with Polynomial Kernel Function and w=L; Fr 1 = sin h 0 ; w=Y 1 and w sin h 0 =Y 1 as input parameters performs better than other models in predicting the discharge coefficient. Where w, L, h 0 , and Y 1 are the height of crest, weir length, oblique side-weir included angle, and upstream flow depth, respectively. Also, the results showed that the SVR model with mean square error (RMSE) of 0.050 performs much better than the two other nonlinear regression published equations with RMSE of 0.121 and 0.4270, respectively.

show abstract

“…The experimental dataset of Borghei and Parvaneh (2011) was used in this study. The main channel was of 11 and 0.4 m in length and width, respectively ( Fig.…”

Section: Experimental Datasetmentioning

confidence: 99%

Section: Determination Of the Best Input Combinationmentioning

confidence: 99%

Section: Determination Of the Best Input Combinationmentioning

confidence: 99%

See 1 more Smart Citation

Optimum Support Vector Regression for Discharge Coefficient of Modified Side Weirs Prediction

Zaji

Bonakdari

2017

INAE Lett

View full text Add to dashboard Cite

show abstract

“…To perform a better comparison of triangular labyrinth, trapezoidal labyrinth, asymmetric labyrinth and rectangular side weirs, part of the experimental data by Borghei and Parvaneh (2011) and Parvaneh et al (2012) is presented in Table 9.…”

mentioning

confidence: 99%

“…Table 9. Range of variables studied by Borghei and Parvaneh (2011) and Parvaneh et al (2012), used in the present discussion …”

mentioning

confidence: 99%