Application of Some Artificial Intelligence Optimization Methods to Determine the Freshness of Eggs

Abstract

Egg quality, can be divided into two groups as internal and external, is evaluated using various methods whether breaking eggs. Image processing makes digital images usable for various purposes such as image compression, image editing, object recognition, face recognition, medical imaging, and many other areas such as the automotive industry. This study aimed to determine the freshness of eggs using different artificial intelligence optimization methods with image processing without breaking the eggs. Artificial neural networks (ANNs), artificial bee colonies, particle swarm optimization, and genetic algorithms were compared using classification coefficients. As a result of the study, it was determined that ANNs, GA, PSO, ABC algorithms had R 2 values of 0.9492, 0.14, 0.07, 0.13, respectively, and ANNs could be used to determine egg freshness. According to the results, it has been understood that the most suitable method for determining egg freshness is artificial neural networks which can be effectively used for this purpose and has sufficient accuracy to be transferred to industrial applications.