• DocumentCode
    3575613
  • Title

    Research on aquatic products safety assessment

  • Author

    Xu, E. ; Wang Xinquan ; Zhang Ye ; Mao Meijing ; Tanyan

  • Author_Institution
    Dept. of Inf. Sci. & Technol., Bohai Univ., Jinzhou, China
  • fYear
    2014
  • Firstpage
    61
  • Lastpage
    64
  • Abstract
    Aquatic product safety assessment is a hot and hard problem in the research field which is one of the important contents in food safety supervision and management, and is composed of all kinds of assessment indexes which are not only dependent, but also independent. To deal with it, a new method was proposed by using core attributes, discernable matrix and so on. Attribute reduction of rough sets is an NP-hard problem, but there is not a popular efficient algorithm presently. The attribute union concept based on the set theory and the attribute reduced algorithm based on this concept were presented. The algorithm translates the attribute reduction to find the attribute union, reducing the number of scanning the decision table and improving the reduced efficiency. The scanning strategy from bottom to top and with width priority can ensure to find the minimal reduction. Also, an example was presented to describe the algorithm.
  • Keywords
    computational complexity; decision tables; food products; food safety; matrix algebra; optimisation; set theory; NP-hard problem; aquatic product safety assessment; attribute union concept; core attributes; decision table scanning strategy; discernable matrix; food safety management; food safety supervision; rough set attribute reduction; set theory; Algorithm design and analysis; Data mining; Decision making; Heuristic algorithms; Information systems; Safety; Set theory; aquatic products; rough set; safety assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Control (ICMC), 2014 International Conference on
  • Print_ISBN
    978-1-4799-2537-7
  • Type

    conf

  • DOI
    10.1109/ICMC.2014.7231517
  • Filename
    7231517