Predictive modeling the side weir discharge coefficient using neural network

Parsaie, Abbas

doi:10.1007/s40808-016-0123-9

Cited by 40 publications

(13 citation statements)

References 33 publications

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“…The soft computing technique is one of the most relevant and modern techniques used in the civil engineering problems (Sihag et al 2018b, c;Nain et al 2018bKisi et al 2017;Parsaie et al 2017c;Kisi et al 2015;Parsaie and Haghiabi 2014;Shiri and Kisi 2012). In this investigation, GP, SVM and M5P tree models were used.…”

Section: Soft Computing Techniquesmentioning

confidence: 99%

“…Tiwari et al (2017) used the generalised regression neural network, MLR, M5P model tree and SVM to predict the cumulative infiltration of soil and found that SVM works well than the other techniques. Various researchers have been used various soft computing techniques in hydraulics and environmental engineering applications (Sihag et al 2017b(Sihag et al , c, 2018aHaghiabi et al 2018;Nain et al 2018a;Tiwari et al 2018;Parsaie et al 2017a, b;Shiri et al 2016Shiri et al , 2017Parsaie andHaghiabi 2015, 2017;Parsaie 2016;Azamathulla et al 2016;Baba et al, 2013). These researchers found that these techniques work exceptionally well.…”

Section: Introductionmentioning

confidence: 99%

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Modelling of the impact of water quality on the infiltration rate of the soil

2019

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The concept behind of this paper is to check the potential of the three regression-based techniques, i.e. M5P tree, support vector machine (SVM) and Gaussian process (GP), to estimate the infiltration rate of the soil and to compare with two empirical models, i.e. Kostiakov model and multi-linear regression (MLR). Totally, 132 observations were obtained from the laboratory experiments, out of which 92 observations were used for training and residual 40 for testing the models. A double-ring infiltrometer was used for experimentation with different concentrations (1%, 5%, 10% and 15%) of impurities and different types of water quality (ash and organic manure). Cumulative time (T f ), type of impurities (I t ), concentration of impurities (C i ) and moisture content (W c ) were the input variables, whereas infiltration rate was considered as target. For SVM and GP regression, two kernel functions (radial based kernel and Pearson VII kernel function) were used. The results from this investigation suggest that M5P tree technique is more precise as compared to the GP, SVR, MLR approach and Kostiakov model. Among GP, SVR, MLR approach and Kostiakov model, MLR is more accurate for estimating the infiltration rate of the soil. Thus, M5P tree is a technique which could be used for modelling the infiltration rate for the given data set. Sensitivity analyses suggest that the cumulative time (T f ) is the major influencing parameter on which infiltration rate of the soil depends.

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Section: Soft Computing Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling of the impact of water quality on the infiltration rate of the soil

2019

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“…Due to high cost of experiments and de ciency in laboratory studies due to simpli cations and limit range of measured parameters, researchers attempt to use the mathematical approaches for modeling and predicting the scour depth at downstream of ip buckets. In the eld of mathematical modeling, using both of CFD and soft computing techniques was reported by Xiao et al [11].Nowadays, by advancing the soft computing techniques in the most areas related to hydraulic engineering, investigators have tried to use these techniques for predicting the scouring phenomena [12][13][14][15][16][17][18][19], speci cally scour depth at downstream of ip bucket. In this regard, using the Arti cial Neural Networks (ANNs), Genetic Programming (GP), Support Vector machine and M5 Model Tree, Group Method of Data Handling (GMDH), and Adaptive Neuro Fuzzy Inference System (ANFIS) can be mentioned [20][21][22][23][24][25][26][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Estimation of scour downstream of a ski-jump bucket using the multivariate adaptive regression splines

Haghiabi

2017

Scientia Iranica

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Abstract. In this paper, modeling the scour downstream of a ip bucket of spillways was considered using empirical formulas, soft computing techniques such as multilayer perceptron (MLP) neural network, and Multivariate Adaptive Regression Splines (MARS). For this purpose, 95 data sets were collected with regard to the most a ective parameters on the scouring phenomena at downstream of spillways. During the MLP model development, it was found that the two transfer functions, such as log-sigmoid and radial basis, had very suitable performances for predicting the desired scouring phenomena. The results of MARS model showed that this model with coe cient of determination 0.99 and 0.91 during the development and testing stages, respectively, had suitable performance for modeling the scouring depth at downstream of ip bucket structure. The results of gamma test and MARS model indicated that q=(gd 3 w ), R=d w , and H=d w were the most a ective parameters on the scouring phenomena.

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“…These formulas have dependable performance for calculating the discharge in normal channel but when floods occur, surplus flow on the capacity of the normal channel flow in floodplains makes using the classical formulas for estimating the discharge of flow unsure. Using them may lead to errors (Ackers 1993;Al-Khatib et al 2012, 2013Azamathulla et al 2016;Dehdar-behbahani and Parsaie 2016;Parsaie and Haghiabi 2014;Parsaie and Haghiabi 2015a, b, c). Several reasons have been reported for the lack reliability of these methods under flood conditions (Bousmar and Zech 1999).…”

Section: Introductionmentioning

confidence: 99%

Flow discharge estimation in compound open channel using theoretical approaches

Parsaie

Najafian

Yonesi

2016

Sustain. Water Resour. Manag.

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Estimating the value of discharge in water ways is an important factor in the flood controlling projects. Recently by advances in flood management, investigators have proposed to use the concept of compound section for modeling the flow characteristics in the natural waterways such as rivers. Several conceptual and theoretical approaches based on the idea of compound section have been proposed for estimating the discharge in rivers. In this study, the performances of the theoretical methods were assessed using performing series of experiments in straight prismatic compound open channel and also analyzing the published data in the literature. Analyzing the performance of theoretical methods shows that Divided Channel Method including vertical bounded line with the determination of coefficient (0.91) and root mean square error (0.02) is an accurate method through the theoretical approaches and only this method has suitable ability to apply for practical purposes.

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Predictive modeling the side weir discharge coefficient using neural network

Cited by 40 publications

References 33 publications

Modelling of the impact of water quality on the infiltration rate of the soil

Modelling of the impact of water quality on the infiltration rate of the soil

Estimation of scour downstream of a ski-jump bucket using the multivariate adaptive regression splines

Flow discharge estimation in compound open channel using theoretical approaches

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