Development of prediction method for the peak harvest day of persimmon using meteorological data and artificial neural networks
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- OKAYAMA Atsushi
- 近畿大学大学院 農学研究科環境管理学専攻
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- YAMAMOTO Atsushi
- 近畿大学大学院
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- KIMURA Masaomi
- 近畿大学大学院
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- MATSUNO Yutaka
- 近畿大学大学院
Bibliographic Information
- Other Title
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- 人工ニューラルネットワークを用いた気象データによるカキの収穫最盛日予測手法の開発
Description
<p>In the Gojo Yoshino area of Nara Prefecture, an excellent persimmon production area, a short-term employment plan has been started around six months before harvest time to secure labour for harvesting work. As global warming makes it difficult to predict the harvest time by empirical methods, a new forecasting method is required. In this study, ANN was used to predict the peak harvest date of persimmon based on meteorological data. The three target varieties were ’Tonewase’, ’Hiratanenashi’ and ’Fuyu’. Model parameters were investigated and a model was constructed for each variety. A model was constructed with an error margin of up to three days. In addition, all three varieties are harvested after October, with a maximum error of 2.5 days as at 1 May and 1 June,errors at the 1st of each month up to just before harvest were found to be predictable by a maximum of three days. The adaptability of ANNs as a method for predicting harvest time was demonstrated.</p>
Journal
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- Artificial Intelligence and Data Science
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Artificial Intelligence and Data Science 4 (3), 46-53, 2023
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1390298124265460992
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- ISSN
- 24359262
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed