Application of genetic frog jumping method in auditing and accounting

Auditing has enjoyed a lot of growth and development in recent years and auditors have beenable to follow organizational effectiveness and growth. The general purpose of the currentresearch is the application of the combined genetic algorithm and neural network method inauditing, and the results were analyzed using the descriptive method that uses meta-histor ica lmodels, and the result is the applicability of these models in auditing. The Frog Hybrid LeapAlgorithm (SFLA) is a metaheuristic memetic-based algorithm. This algorithm was developed in recent years by Eusuff and Lansey. The SFLA algorithm originates from the way groups of frogs search for food. This algorithm uses memetic evolution method for local search among frog subgroups. SFLA uses a combination strategy and enables message exchange in local searches. This algorithm combines the advantages of memetic growth algorithm and particle group optimization. In SFLA, messages are exchanged not only in local search but also in global search. In this way, local and global search are well combined in this algorithm. Local search enables the transfer of memes among individuals, and the combination strategy enables the transfer of memes among the entire population. Similar to Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), Frog Hybrid Mutation Algorithm is a colony-based optimiza tio n algorithm. SFLA is highly capable of global search and is easy to implement.

Keywords:

Accounting , auditing , frog jumping , hybrid algorithm