Advertisement
Published in:
2011 | OriginalPaper | Chapter
Data Mining for Seasonal Influences in Broiler Breeding Based on Observational Study
Authors : Peijie Huang, Piyuan Lin, Shangwei Yan, Meiyan Xiao
Published in: Information Computing and Applications
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.