{"title":"基于模拟退火算法的Blumberg模型参数估计:以肉鸡体重为例","authors":"Wahyudin Nur, Darmawati","doi":"10.31605/jomta.v5i1.1762","DOIUrl":null,"url":null,"abstract":"The Blumberg model is one of the logistic models. The advantage of the Blumberg model is the flexibility of the inflection point. The Blumberg model is believed to be suitable for modeling the growth of living organs. In this article, we estimate the parameters of the Blumberg model using simulated annealing algorithm. The simulated annealing algorithm is a heuristic optimization method based on the metal annealing process. The data used is Broiler daily weight data. The model obtained fits the daily weight data of Broiler. Our results show that the closer the cooling schedule factor to 1, the smaller the error. In addition, we must carefully select the initial temperature. The selection of the initial temperature that is not suitable drives the error to enlarge.","PeriodicalId":313373,"journal":{"name":"Journal of Mathematics: Theory and Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Parameter Estimation of The Blumberg Model Using Simulated Annealing Algorithm: Case Study of Broiler Body Weight\",\"authors\":\"Wahyudin Nur, Darmawati\",\"doi\":\"10.31605/jomta.v5i1.1762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Blumberg model is one of the logistic models. The advantage of the Blumberg model is the flexibility of the inflection point. The Blumberg model is believed to be suitable for modeling the growth of living organs. In this article, we estimate the parameters of the Blumberg model using simulated annealing algorithm. The simulated annealing algorithm is a heuristic optimization method based on the metal annealing process. The data used is Broiler daily weight data. The model obtained fits the daily weight data of Broiler. Our results show that the closer the cooling schedule factor to 1, the smaller the error. In addition, we must carefully select the initial temperature. The selection of the initial temperature that is not suitable drives the error to enlarge.\",\"PeriodicalId\":313373,\"journal\":{\"name\":\"Journal of Mathematics: Theory and Applications\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mathematics: Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31605/jomta.v5i1.1762\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematics: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31605/jomta.v5i1.1762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parameter Estimation of The Blumberg Model Using Simulated Annealing Algorithm: Case Study of Broiler Body Weight
The Blumberg model is one of the logistic models. The advantage of the Blumberg model is the flexibility of the inflection point. The Blumberg model is believed to be suitable for modeling the growth of living organs. In this article, we estimate the parameters of the Blumberg model using simulated annealing algorithm. The simulated annealing algorithm is a heuristic optimization method based on the metal annealing process. The data used is Broiler daily weight data. The model obtained fits the daily weight data of Broiler. Our results show that the closer the cooling schedule factor to 1, the smaller the error. In addition, we must carefully select the initial temperature. The selection of the initial temperature that is not suitable drives the error to enlarge.