Keywords : Boltzmann Distribution


Using Genetic Algorithm to Estimate (RNA) Estimator

Ban Ahmed Mitras; Farah Saad Nashat

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 3, Pages 145-160
DOI: 10.33899/csmj.2010.163934

In this paper the genetic algorithm has been used to estimate the parameter θ which exist in Boltzmann Distribution which controls the structure of the Ribo Nucleic Acid (RNA). Two algorithms have been suggested. The first found the value of the estimator which maximizes the likelihood function of Boltzmann Distribution. The second minimized the generation constraint of Boltzmann Distribution by using the genetic algorithm. Matlab (7.0) has been used in writing the programs of  algorithms and achieved the following results: The maximum value for the likelihood estimator for Boltzmann Distribution appear at the value -4.1614 where the value of θ is 0.1457, and the minimum value for the Constraint Generation for Boltzmann Distribution appear at the value 0.951039101*17  where the value of θ is -4.4066.