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Genetic Programming for Bee Audio Classification

Published: 13 July 2023 Publication History

Abstract

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.

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ICIIT '23: Proceedings of the 2023 8th International Conference on Intelligent Information Technology
February 2023
310 pages
ISBN:9781450399616
DOI:10.1145/3591569
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 13 July 2023

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Author Tags

  1. Audio classification
  2. Convolutional neural networks
  3. Genetic programming
  4. Machine learning
  5. Parameter setting

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