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Title: Prediction of Dynamical Properties of Flow Over a Three-element Airfoil via Computationally Intelligent Architectures
Authors: Kasnakoğlu, Coşku
Efe, Mehmet Önder
Keywords: computational intelligence
artificial neural networks
air flow
pressure prediction
velocity prediction
multilayer perceptron
adaptive neuro fuzzy inference system
radial Basis function neural network
least squares support vector machine
Issue Date: 2008
Publisher: IEEE
Source: International Conference on Control, Automation and Systems -- OCT 14-17, 2008 -- Seoul, SOUTH KOREA
Abstract: In this paper we study various computationally intelligent architectures for prediction of pressure values and velocity components of flow past a three-element airfoil. Six sensor locations are selected around the airfoil and the goal is to predict the flow behavior at the rear of the airfoil using pressure readings from the remaining five sensors. To make the problem more interesting we require the predictor to estimate the flow twenty time steps ahead of current time. Data is collected from CFD simulations of the flow and predictors are built using four different computationally intelligent architectures: Multilayer Perceptron (MLP), Adaptive Neuro Fuzzy Inference System (ANFIS), Radial Basis Function Neural Network (RBFNN), and Least Squares Support Vector Machine (LS-SVM). Levenberg-Marquardt optimization technique is utilized for parameter tuning purposes. In addition, a simple linear predictor is built as a benchmark for comparing the MLP, ANFIS, RBFNN, and LS-SVM based predictors. It is observed that MLP and ANFIS based predictors achieve the best prediction, and the performace of all predictors are superior to that of the simple linear predictor.
ISBN: 978-89-950038-9-3
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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