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Data Mining for Seasonal Influences in Broiler Breeding Based on Observational Study

  • Peijie Huang
  • Piyuan Lin
  • Shangwei Yan
  • Meiyan Xiao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7030)

Abstract

For the modern poultry breeding companies, it is worthwhile to extract valuable knowledge from the massive historical data to help future production and management. However, data analysis and mining of poultry raising dataset is a challenge due to the complexity and uncertainty bring by the influence of environmental and physiological factors. In this paper, data mining based on observational study is proposed for the research of seasonal influences in broiler breeding. Systematic observational study with the statistical analysis and data mining technology is adopted including macro analysis, exploratory data analysis, and modeling and prediction. Case study using the broiler growth dataset of the most famous poultry raising company in China shows the effectiveness of our approach.

Keywords

Observational study Data mining Seasonal influences Broiler breeding 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Peijie Huang
    • 1
  • Piyuan Lin
    • 1
  • Shangwei Yan
    • 1
    • 2
  • Meiyan Xiao
    • 1
  1. 1.College of InformaticsSouth China Agricultural UniversityGuangzhouChina
  2. 2.Information CentreGuangdong Wens Food Group Limited CompanyXinXingChina

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