Genetic Programming for Bee Audio Classification

Honey bees (Apis mellifera) play a very important role in agriculture thanks to their ability of plants' pollination. However, the number of honey bees decreases every year because of the effects of climate change, environmental pollution, and so on. As a result, finding a useful solution to this problem has been more and more attracting scientists and companies. Applying machine learning (ML) methods based on audio data recording inside the hive is a promising solution to detect changes in the beehive. In this study, we investigate the genetic programming (GP) method, one of the powerful ML methods, for identifying bee sound data. We also compare our proposal with the results from a previous study. The experiment results show that with the right configuration of parameters, GP can achieve better results than well-known methods for the task of classifying bee sound samples. © 2023 ACM.