Journal of Biomedical Fuzzy Systems Association
Online ISSN : 2424-2578
Print ISSN : 1345-1537
ISSN-L : 1345-1537
Integrated Management in Agriculture for Areas without Historical Data
Yasunari MAEDA
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2023 Volume 24 Issue 2 Pages 23-34

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Abstract
There is a lot of previous research on profit maximization in agriculture. In a previous research crop rotation problem and cultivation management problem are solved as one integrated management problem in order to maximize the profit in agriculture. In the previous research the profit is maximized under the condition that probabilities are known. Sufficient historical data is required to estimate probabilities. The previous method cannot be applied to areas where there is no historical data. In this research, a new integrated management method for areas where there is no historical data is proposed. Integrated management is modeled by Markov decision processes with unknown probabilities. Historical data of neighboring areas is used. The proposed method maximizes profit with reference to a Bayes criterion by dynamic programming. In the numerical calculation results, adaptive crop selection and cultivation action selection according to posterior probabilities for neighboring areas are confirmed. This research is a basic research, and future extended research is required.
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© 2023 Biomedical Fuzzy Systems Association
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