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Predicting Calving Time of Dairy Cows by Time Series Model
http://hdl.handle.net/10458/00010275
http://hdl.handle.net/10458/0001027505a20ce7-f3be-416b-b541-e0f2109236e2
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文 (1.2 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2021-10-26 | |||||
| タイトル | ||||||
| タイトル | Predicting Calving Time of Dairy Cows by Time Series Model | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Calving time | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Prediction | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Exponential Distribution Probability | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | ARIMA Modeling | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| 著者 |
Tunn, Cho Lwin
× Tunn, Cho Lwin× Thi, Thi Zin× Yokota, Mitsuhiro |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Calving time prediction is an important factor in dairy farming. The careful monitoring of cows can help to decrease the loss of calf rates during the calving time; moreover, to know the exact time of birth is crucial to make sure timely assistance. However, direct visual observation is time-wasting, and the continuous presence of observers during calving time may disturb cows. Therefore, in this study, the recording from video cameras and counting the number of standing to lying and lying to standing transitions of 25 cows before 72 hours of calving time are used. The time series approaches namely the exponential distribution probability and autoregressive integrated moving average (ARIMA) model are applied to predict the calving time and the root mean square error (RMSE) is used to check the accuracy and error value of the experiment. By these methods, the calving time is predicted with exact time interval by using exponential probability. Moreover, the ARIMA model is better accuracies in predicting calving time than autoregressive (AR) and moving average (MA) models. |
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| 言語 | en | |||||
| 書誌情報 |
ja : 宮崎大学工学部紀要 en : Memoirs of Faculty of Engineering, University of Miyazaki 巻 50, p. 87-94, 発行日 2021-09-28 |
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| 出版者 | ||||||
| 出版者 | 宮崎大学工学部 | |||||
| 言語 | ja | |||||
| 出版者 | ||||||
| 出版者 | Faculty of Engineering, University of Miyazaki | |||||
| 言語 | en | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 05404924 | |||||
| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA00732558 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
