Applications of improved SVM framework in modeling in mechanics

• Autorzy: Pagalthivarthi K. V. , Mittal A. , Goyal P. , Gupta G. R.
• Języki publikacji: EN

Abstrakty

EN

The problem of empirical data modeling is pertinent to several mechanics domains. Empirical data modeling involves a process of induction to build up a model of the system from which responses of the system can be deduced for unobserved data. Machine learning tools can model underlying non-linear function given training data without imposing prior restriction on the type of function. In this paper, we show how Support Vector Machines (SVM) can be employed to solve design problems involving optimizations over parametric space and parameter prediction problems that are recurrent in engineering domain. The problem considered is diffuser design where the optimal value of pressure recovery parameter can be obtained very efficiently by SVM based algorithm even in a large search space. In addition, locating the position of points on a string vibrating in a damped medium serves as an appropriate prediction problem. A grid-searching algorithm is proposed for automatically choosing the best parameters of SVM, thus resulting in a generic framework. The results obtained by SVM are shown to be theoretically sound and a comparison with other approaches such as spline interpolation and Neural Networks shows the superiority of our framework.

Słowa kluczowe

EN

conical diffuser; turbulent flow; string vibration; support vector machine (SVM); parameter grid searching; optimal pressure recovery; neural networks

PL

dyfuzor; sieć neuronowa; metoda wektorów nośnych

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2007
• Tom: Vol. 14, No. 3
• Strony: 509--523
• Opis fizyczny: Bibliogr. 26 poz., rys., tab., wykr.

Twórcy

autor

Pagalthivarthi K. V.

autor

Mittal A.

autor

Goyal P.

autor

Gupta G. R.

• Indian Institute of Technology, Dept. of Applied Mechanics, New Delhi 110016

Bibliografia

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