Determination Discharge Capacity of Triangular Labyrinth Side Weir Using Multi-Layer Neural Network (ANN-MLP)
نویسندگان
چکیده
منابع مشابه
Determination Discharge Capacity of Triangular Labyrinth Side Weir using Multi-Layer Neural Network (ANN-MLP)
Side weirs are used in open channels to control flood and the flow passing through it. Discharge capacity is one of the crucial hydraulic parameters of side weirs. The aim of this study is to determine the effect of the intended dimensionless parameters on predicting the discharge coefficient of triangular labyrinth side weir. MAPE, RMSE, and R2 statistic indexes have been used to assess the ac...
متن کاملPredicting the side weir discharge coefficient using the optimized neural network by genetic algorithm
Side weir is one of the structures which are widely used in water engineering projects So study on the flow characteristics especially discharge coefficient (Cdsw ) of this type of weir is important. Several Empirical formulas proposed to calculate the Cdsw that they usually associated with significant errors. Thus, using mathematical methods based on artificial intelligence is inevitable. Arti...
متن کاملNumerical study of flow of labyrinth weir with triangular and curved plan form using Fluent software
Labyrinth weirs have not a straight crest in the perpendicular direction to the flow. The plan view of the weir consists of multiple and broken linear crests that cause the increase of its effective length. The advantages of this type of weirs are higher discharge capacity, easy aeration as well as low fluctuations of water surface at the weir upstream. This paper deals with the simulation of t...
متن کاملModeling Discharge Coefficient of Side Weir on Converging Channel Using Extreme Learning Machine
In this study, the discharge coefficient of side weirs located on converging channels was simulated for the first time using a new method of Extreme Learning Machine (ELM). To examine the accuracy of the numerical model, the Monte Carlo simulations were used and the experimental values validation was conducted by the k-fold cross validation method. Then, the input parameters were detected for s...
متن کاملBayesian learning in multi-layer perceptron neural network using Monte Carlo: mlp-mc-1
A Bayesian implementation of learning in neural networks using Monte Carlo sampling has been developed by Neal (1996). This computation intensive method has shown encouraging performance in (Neal 1996) and in a study using several datasets in (Rasmussen 1996). For a full description of the method the reader is referred to (Neal 1996). Here a brief description of the algorithm will be given, alo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Current World Environment
سال: 2015
ISSN: 0973-4929,2320-8031
DOI: 10.12944/cwe.10.special-issue1.16