Solving variational and Cauchy problems with self-configuring genetic programming algorithm
by Sergey V. Burakov; Eugene S. Semenkin
International Journal of Innovative Computing and Applications (IJICA), Vol. 5, No. 3, 2013

Abstract: It is suggested to use genetic programming techniques for solving Cauchy problem and variational problem that allows getting the exact analytical solution if it does exist and an approximate analytical expression otherwise. Features of solving process with this approach are considered. Results of numerical experiments are given. The approach improvement is fulfilled by adopting the self-configuring genetic programming algorithm that does not require extra efforts for choosing its effective settings but demonstrates the competitive performance.

Online publication date: Thu, 31-Jul-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Innovative Computing and Applications (IJICA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com