Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of parameters to tune. This paper presents a detailed review of DE parameter tuning with a table compromised a recommended guidelines for these parameters, along with a full description of the basic DE algorithm and its corresponding operators, overlooked by previous studies. It is aimed at practitioners to help them achieve better results when adopting DE as an optimization method for their problems with less time and effort. Moreover, an experimental study has been conducted over fifteen test problems and the results obtained prove the reliability of the setting values.
In this work, an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.
In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.
The identification of salinity-tolerance genes is a critical aspect of the new molecular technology. In this work cDNA-RAPD is used for the identification of genes expressed in salt tolerant but not in salt sensitive wheat. Two cultivars wheat, salt tolerance (Dijla) and sensitive (Tamooz2) were used for the preparation of RNA and cDNA synthesis. Eight primers were used for random amplification of cDNA constructed from RNA and three primers were differentially expressed in salt tolerant cultivars. Genes related to salt tolerant were predicted using NCBI blast for the three primers. The predicted genes were involved in salt tolerance of wheat and other plants as well. This indicates the suitability of the primers and the method for
... Show MoreNonlinear differential equation stability is a very important feature of applied mathematics, as it has a wide variety of applications in both practical and physical life problems. The major object of the manuscript is to discuss and apply several techniques using modify the Krasovskii's method and the modify variable gradient method which are used to check the stability for some kinds of linear or nonlinear differential equations. Lyapunov function is constructed using the variable gradient method and Krasovskii’s method to estimate the stability of nonlinear systems. If the function of Lyapunov is positive, it implies that the nonlinear system is asymptotically stable. For the nonlinear systems, stability is still difficult even though
... Show MoreThe concern of this article is the calculation of an upper bound of second Hankel determinant for the subclasses of functions defined by Al-Oboudi differential operator in the unit disc. To study special cases of the results of this article, we give particular values to the parameters A, B and λ
Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.