Inverse Modeling: Theory and Engineering Examples University of Toledo

Format:

Conference/Event

Author/Creator:

Yarlagadda, Yarlagadda, author.

Contributor:

Devabhaktuni, Vijay Kumar

Nikolaidis, Efstratios

Conference Name:

SAE 2016 World Congress and Exhibition (2016-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2016

Summary:

AbstractOver the last two decades inverse problems have become increasingly popular due to their widespread applications. This popularity continuously demands designers to find alternative methods, to solve the inverse problems, which are efficient and accurate. It is important to use effective techniques that are both accurate and computationally efficient. This paper presents a method for solving inverse problems through Artificial Neural Network (ANN) theory. The paper also presents a method to apply Grey Wolf optimizer (GWO) algorithm to inverse problems. GWO is a recent optimization method producing superior results. Both methods are then compared to traditional methods such as Particle Swarm Optimization (PSO) and Markov Chain Monte Carlo (MCMC). Four typical engineering design problems are used to compare the four methods. The results show that the GWO outperforms other methods both in terms of efficiency and accuracy. The error is comparable among the ANN and PSO methods, while the latter has better computational efficiency

Notes:

Vendor supplied data

Publisher Number:

2016-01-0267

Access Restriction:

Restricted for use by site license