文章基本信息

标题：An Amazon stingless bee foraging activity predicted using recurrent artificial neural networks and attribute selection
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作者：Pedro A. B. Gomes ; Yoshihiko Suhara ; Patrícia Nunes-Silva 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2020
卷号：10
期号：1
页码：1-12
DOI：10.1038/s41598-019-56352-8
出版社：Springer Nature
摘要：Bees play a key role in pollination of crops and in diverse ecosystems. There have been multiple reports in recent years illustrating bee population declines worldwide. The search for more accurate forecast models can aid both in the understanding of the regular behavior and the adverse situations that may occur with the bees. It also may lead to better management and utilization of bees as pollinators. We address an investigation with Recurrent Neural Networks in the task of forecasting bees' level of activity taking into account previous values of level of activity and environmental data such as temperature, solar irradiance and barometric pressure. We also show how different input time windows, algorithms of attribute selection and correlation analysis can help improve the accuracy of our model.