کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11019849 | 1717619 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Neural predictive control of broiler chicken and pig growth
ترجمه فارسی عنوان
کنترل پیش بینی عصبی جوجه های گوشتی و رشد خوک
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کلمات کلیدی
کنترل پیش بینی جوجه گوشتی خوک، رشد شناسایی سیستم، مدل شبکه عصبی،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
چکیده انگلیسی
Active control of the growth of broiler chickens and pigs has potential benefits for farmers in terms of improved production efficiency, as well as for animal welfare in terms of improved leg health in broiler chickens. In this work, a differential recurrent neural network (DRNN) was identified from experimental data to represent animal growth using a nonlinear system identification algorithm. The DRNN model was then used as the internal model for nonlinear model predictive control (NMPC) to achieve a group of desired growth curves. The experimental results demonstrated that the DRNN model captured the underlying dynamics of the broiler and pig growth process reasonably well. The DRNN based NMPC was able to specify feed intakes in real time so that the broiler and pig weights accurately followed the desired growth curves ranging from â12% to +12% and â20% to +20% of the standard curve for broiler chickens and pigs, respectively. The overall mean relative error between the desired and achieved broiler or pig weight was 1.8% for the period from day 12 to day 51 and 10.5% for the period from week 5 to week 21, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosystems Engineering - Volume 173, September 2018, Pages 134-142
Journal: Biosystems Engineering - Volume 173, September 2018, Pages 134-142
نویسندگان
Theo G.M. Demmers, Yi Cao, Sophie Gauss, John C. Lowe, David J. Parsons, Christopher M. Wathes,