jzs-10823

Estimating the Parameter of RNA by using Hybrid Bat with Modified CG Algorithms

Ban Ahmed Mitras1 and Borhan F. Jumaa*2

1Department of mathematics, college of computer sciences & mathematics, Mosul University

2Department of Computer sciences, college of computer sciences & I.T., Kirkuk University

*Corresponding author’s e-mail: borhan_nissan@yahoo.com 

Original: 20 April 2020        Revised: 21 August 2020        Accepted: 26 September 2020        Published online: 20 December 2020  

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Abstract

In this research, one of the flock algorithms hybridized which the algorithm of flock of Bat’s examples with a traditional modified method that is the conjugate gradient method where it modified by deriving new conjugate coefficient. The sufficient descent and the global convergence properties for the proposed algorithm proved, and each of the thorough approximation and descending qualities illustrated for the coefficient that derived. The numeral results on test functions showed the efficiency of the hybrid algorithm on each of flock of Bats and conjugate gradient original algorithms. The hybrid algorithm was also to estimate the parameter θ that exist in Boltzmann distribution that controls the structure of the Ribo Nucleic Acid (RNA). This paper dealt with estimation of the parameter of Boltzmann's Distribution by using the hybrid algorithm. The results of the hybrid algorithm were encouraged. 

Key Words: Conjugate gradient methods, meta-heuristic algorithms, BAT algorithm

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