Why Estimation Method of Recurrence Time Transition Probabilities with Regard to Genetic Algorithms Without Bit Mutation?

  • Usama Hanafy Abou El-Enien The High Institute for Tourism, Hotels & Computer, El-Seyouf, Alexandria
Keywords: Genetic Algorithms without Bit Mutation, Recurrence Time

Abstract

Respecting genetic algorithms without bit mutation, our study is to submit unprecedented algorithm to procure tentative and notional results respecting recurrence time transition probabilities estimation for transient states.    

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Author Biography

Usama Hanafy Abou El-Enien, The High Institute for Tourism, Hotels & Computer, El-Seyouf, Alexandria

Administrative Information Systems Department, The High Institute for Tourism, Hotels & Computer,

El-Seyouf,  Alexandria, Egypt

References

El-Nady Kh., Abou El-Enien U., Badr A. (2011). Why are genetic algorithms MCMC2 Markov Chain Monte Carlo. AMSE Journals, Advances in Modelling and Analysis B 54(1): 1-16.

Abou El-Enien U. (2015). Why unified statistics theory by MCMC towards estimation of stationary transition probabilities of stochastic matrix?. Journal of Computer and Mathematical Sciences 6(7): 411-415.

Abou El-Enien U. (2012). A new unified MCMC methods toward unified statistics theory by MCMC. LAP, Germany.

Published
2019-08-30
How to Cite
Abou El-Enien, U. H. (2019). Why Estimation Method of Recurrence Time Transition Probabilities with Regard to Genetic Algorithms Without Bit Mutation? . Computer Reviews Journal, 4, 144-145. Retrieved from http://purkh.com/index.php/tocomp/article/view/465
Section
Research Articles