A Machine Learning Approach to Forecasting Honey Production with Tree-Based Methods

• URL: http://arxiv.org/abs/2304.01215v1
• Date: Thu, 30 Mar 2023 07:21:51 GMT
• Title: A Machine Learning Approach to Forecasting Honey Production with Tree-Based Methods
• Authors: Alessio Brini, Elisa Giovannini, Elia Smaniotto
• Abstract summary: We disentangle the honey production drivers with tree-based methods and predict honey production variations for hives in Italy. The database covers hundreds of beehive data from 2019-2022 gathered with advanced precision beekeeping techniques.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The beekeeping sector has undergone considerable production variations over the past years due to adverse weather conditions, occurring more frequently as climate change progresses. These phenomena can be high-impact and cause the environment to be unfavorable to the bees' activity. We disentangle the honey production drivers with tree-based methods and predict honey production variations for hives in Italy, one of the largest honey producers in Europe. The database covers hundreds of beehive data from 2019-2022 gathered with advanced precision beekeeping techniques. We train and interpret the machine learning models making them prescriptive other than just predictive. Superior predictive performances of tree-based methods compared to standard linear techniques allow for better protection of bees' activity and assess potential losses for beekeepers for risk management.

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