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In order to address the lack of available growth data for pigs, we generate a synthetic dataset describing the weight of swine in relation to environmental factors based on the theoretical growth model and experimentally measured data, in an attempt to facilitate the application of machine learning techniques. Using the generated growth data, linear regression, tree regression, adaptive boosting (AdaBoost), and a deep neural network (DNN) are applied to estimate ADG. By means of a performance evaluation, we confirm that the machine learning algorithms are capable of predicting the ADG of swine accurately even when the growth characteristics of pigs are heterogeneous, i.e., each pig follows a different growth curve. Moreover, we also find that DNN can provide a higher predictive accuracy than other machine learning-based schemes.<\/jats:p>","DOI":"10.3233\/jifs-169869","type":"journal-article","created":{"date-parts":[[2018,11,9]],"date-time":"2018-11-09T15:15:34Z","timestamp":1541776534000},"page":"923-933","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Prediction of average daily gain of swine based on machine learning"],"prefix":"10.1177","volume":"36","author":[{"given":"Woongsup","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Information and Communication Engineering, Institute of Marine Industry, Gyeongsang National University, Tongyeong, Republic of Korea"}]},{"given":"Kang-Hwi","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Institute of Marine Industry, Gyeongsang National University, Tongyeong, Republic of Korea"}]},{"given":"Hyeon Tae","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Bio-Industrial Machinery Engineering, Institute of Agriculture &amp; Life Science, Gyeongsang National University, Jinju, Gyeongnam, Republic of Korea"}]},{"given":"Heechul","family":"Choi","sequence":"additional","affiliation":[{"name":"Livestock environment division, National Institue of Animal Science, Kongjwipatjwi, lseo, Wanju, JeonBuk, Republic of Korea"}]},{"given":"Younghwa","family":"Ham","sequence":"additional","affiliation":[{"name":"Agrirobotech Co., Ltd., Sina-ro, Bubal-eup, Icheon-si, Gyeonggi-do, Republic of Korea"}]},{"given":"Tae-Won","family":"Ban","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Institute of Marine Industry, Gyeongsang National University, Tongyeong, Republic of Korea"}]}],"member":"179","published-online":{"date-parts":[[2018,11,8]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.5713\/ajas.2005.590"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.5187\/JAST.2013.55.3.195"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.4141\/A00-006"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.2527\/1991.692726x"},{"key":"e_1_3_2_6_2","volume-title":"Modeling Growth of Pigs Reared to Heavy Weights","author":"Shull C.M.","year":"2015","unstructured":"C.M.Shull, Modeling Growth of Pigs Reared to Heavy Weights, Ph. 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