Proactive model to predict and notify the risk of CRD problem in broiler farms

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Author listManeewongvatana S., Maneewongvatana S.

PublisherHindawi

Publication year2013

Start page47

End page51

Number of pages5

ISSN0146-9428

eISSN1745-4557

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84899430637&doi=10.1109%2fICAwST.2013.6765407&partnerID=40&md5=72e9c143a55e36142c6b20fe32f05033

LanguagesEnglish-Great Britain (EN-GB)


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Abstract

CRD (Chronic Respiratory Disease) is the main cause of rejection in broiler farm industry. The large number of CRD rejections is due to the difficulty in determining root causes of disease. Moreover, this disease is very hard to be observed from outside. Hence, farmers cannot setup strategy to prevent or reduce the large number of infected chickens in time. This project proposed the proactive model for predicting the number of infected chickens by association rules technique that can continually predict the number of CRD rejections in every state of broiler raising cycle. The rules are generated from historical data and the set of risk parameters for a specific farm is extracted. Hence, for each state, farmers can obtain the notification if they have a risk to have high CRD infection. Moreover, the suggestion and avoidance to prevent the CRD problem is discovered based on the set of risk parameters of the current state. This strategy can help farmers to reduce the rate of CRD infection in time. ฉ 2013 IEEE.


Keywords

Association RulesCRDModel prediction


Last updated on 2023-29-09 at 07:35