Concept drift for CRD prediction in broiler farms

Conference proceedings article

Authors/Editors

Strategic Research Themes

No matching items found.

Publication Details

Author list: Channoi K., Maneewongvatana S.

Publisher: Hindawi

Publication year: 2015

Start page: 287

End page: 290

Number of pages: 4

ISBN: 9781479919659

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945935353&doi=10.1109%2fJCSSE.2015.7219811&partnerID=40&md5=9475f9405b195a9870c506a43de47cdb

Languages: English-Great Britain (EN-GB)

View on publisher site

Abstract

Chronic Respiratory Disease (CRD) is a serious problem in broiler farms and food production industry. This disease cannot be observed easily during the broiler raised process. The model for predicting CRD rate is not exactly identified, because of the variation in farm environment and the development of breeding. Therefore the embedded of concept drift to the normal predictor is the possible way to build the system that can detect the change in data stream and build the suitable predictor for the current information. In this work we applied the method of concept drift to the basic Na๏ve Bayes classifier to predict the CRD rate by using the data collected from many contract farms during the entire raising period. The experimental result shows that, with the concept drift embedded method, the accuracy of prediction is improved by about 30%. ฉ 2015 IEEE.

Keywords

Broiler Farm Industry, Concept drift, CRD