Genetic Algorithm based Mathematical Model for Students Performance in Examination

Genetic Algorithm (GA) is one of major theoretical mathematical method to simulate development of biological. That is majorly utilized in various areas like medicine, engineering and economics. The GA is used as mathematical method basis for optimization in students' performance in examination. The selection technique through competition is taken for electing random crossover of male crossover possibility with huge similarity for producing new population. In this research, GA is proposed for adjusting possibility of crossover and dynamic mutation in accordance with fitness which aimed to solve dynamic changes issue. The analysis of method is done among nonlinear differential equations and Levenberg-Marquardt technique. The method enhancement is attained after analyzing the process of operation and architecting the classical GA, mathematical method application has enhancement in accuracy method determined through GA. The improved optimization methods are analyzed and verified through GA and proved the research outcome feasibility. The proposed GA has less error rates than other existing algorithms like Back Propagation (BP) and Levenberg-Marquardt techniques.