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AL-Rafidain Journal of Computer Sciences and Mathematics

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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
10.33899/csmj.2010.163934

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Abstract

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.
 
Keywords:
    Genetic algorithm Boltzmann Distribution RNA Estimator
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(2010). Using Genetic Algorithm to Estimate (RNA) Estimator. AL-Rafidain Journal of Computer Sciences and Mathematics, 7(3), 145-160. doi: 10.33899/csmj.2010.163934
Ban Ahmed Mitras; Farah Saad Nashat. "Using Genetic Algorithm to Estimate (RNA) Estimator". AL-Rafidain Journal of Computer Sciences and Mathematics, 7, 3, 2010, 145-160. doi: 10.33899/csmj.2010.163934
(2010). 'Using Genetic Algorithm to Estimate (RNA) Estimator', AL-Rafidain Journal of Computer Sciences and Mathematics, 7(3), pp. 145-160. doi: 10.33899/csmj.2010.163934
Using Genetic Algorithm to Estimate (RNA) Estimator. AL-Rafidain Journal of Computer Sciences and Mathematics, 2010; 7(3): 145-160. doi: 10.33899/csmj.2010.163934
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