کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6539327 | 1421097 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new method to learn growth curves of beef cattle using a factorization approach
ترجمه فارسی عنوان
یک روش جدید برای یادگیری گاوهای گوشتی با استفاده از رویکرد فاکتور
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کلمات کلیدی
سیستم توصیهگر، تقسیم ماتریس، فرود شیبدار، منحنی رشد، گاو گوشت گاو،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
The evolution of cattle weight is a very important issue for beef cattle breeders. The weights of the animals of a herd are usually available at different ages and it is intended to predict the trajectory that will follow the weight of each animal. In this paper, we address this problem as a Recommender System. In this case, the users would be the animals, and the items would be the ages of weight measurements. The values of the items would be the measured weights at a given age. As in Recommender Systems the aim is to complete the valuation matrix (weights) in an individualized way (that is, adapted to each animal). A matrix factorization system is devised to learn weights using all the available characteristics of the animals. The weights thus obtained are compared with a linear regression that adequately estimates the general evolution of the herd, but not the individual evolution of each animal. To illustrate the benefits of this approach, we used a real world dataset of cattle of the breed Avileña-Negra Ibérica and crossbreeding with sires of Charolais and Limousin.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 151, August 2018, Pages 77-83
Journal: Computers and Electronics in Agriculture - Volume 151, August 2018, Pages 77-83
نویسندگان
Jaime Alonso, Jorge DÃez, Oscar Luaces, Antonio Bahamonde,