Applying simulated annealing as an intelligent genetic mutation operator for finding most probable explanations on Bayesian belief networks

Author

Sahr Attia Afara, The American University in Cairo AUC

School

School of Sciences and Engineering

Degree Name

MS in Computer Science

First Advisor

Dr. Asraf Abdelbar

Committee Member 1

Dr. Mohamad Fahmy Tolha

Committee Member 2

Dr. Mohamed Mohy Mohamed

Document Type

Thesis

Rights

The American University in Cairo grants authors of theses and dissertations a maximum embargo period of two years from the date of submission, upon request. After the embargo elapses, these documents are made available publicly. If you are the author of this thesis or dissertation, and would like to request an exceptional extension of the embargo period, please write to thesisadmin@aucegypt.edu

Recommended Citation

APA Citation

Afara, S. A. ().Applying simulated annealing as an intelligent genetic mutation operator for finding most probable explanations on Bayesian belief networks [Thesis, the American University in Cairo]. AUC Knowledge Fountain.
https://fount.aucegypt.edu/retro_etds/2615

MLA Citation

Afara, Sahr Attia. Applying simulated annealing as an intelligent genetic mutation operator for finding most probable explanations on Bayesian belief networks. . American University in Cairo, Thesis. AUC Knowledge Fountain.
https://fount.aucegypt.edu/retro_etds/2615

Call Number

Thesis 2000/27

Location

mgfth