Fred Petry

Dr. Fred Petry


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 May 2004 in International Journal of Intelligent Systems
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Journal Article
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TBTheresa Beaubouef
Theresa Beaubouef
RLRoy Ladner
Roy Ladner
Fred PetryFred Petry
Fred Petry
Uncertainty management is necessary for real world applications, especially those used with data mining. The Region Connection Calculus (RCC) and egg-yolk methods have proven useful for the representation of vague regions in spatial data. Rough set theory has been shown to be an effective tool for data mining and for uncertainty management in databases. In this study we use a rough set foundation for expressing topological relationships previously defined for the RCC and egg-yolk methods and show that rough sets can improve on the representation of topological relationships and concepts defined with the other models, which leads to improved mining of spatial data. Finally, we provide an extension of spatial association rule generation that will be able to use rough set–modeled spatial data.

16 March 2014 in Journal of Ambient Intelligence and Humanized Computing
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Journal Article
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PEPaul Elmore
Paul Elmore
Fred PetryFred Petry
Fred Petry
RYRonald Yager
Ronald Yager
Uncertainty must be taken into account in all aspects of ambient intelligence and human decisions and activities. We investigate how to utilize both probabilistic and possibilistic sources of information for use in humanized decision-making. In particular we examine aspects of the possibilistic conditioning of probability developed by Yager. To provide bounding of the resulting probability analysis of the cases of completely certain and uncertain probability and possibility distribution are carried out. Additionally the cases of intermediate uncertainty and a general case of possibilities are analyzed. The Zadeh consistency measure is also used to assess these cases. To consider whether the conditioned probability is more informative for decision-making, three measures, Shannon entropy, Gini index and Renyi entropy are used to compare the original probability distributions and the conditioned distribution for the cases described.

1 May 2009 in Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Journal Article
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TBTheresa Beaubouef
Theresa Beaubouef
Fred PetryFred Petry
Fred Petry
This paper introduces the intuitionistic rough set and intuitionistic rough relational and rough object oriented database models. Rough set, fuzzy set, and intuitionistic set uncertainty management are discussed and compared, and the model based on intuitionistic and rough sets developed here is applied to databases. The intuitionistic rough set database models draw benefits from both the rough set and intuitionistic techniques, providing greater management of uncertainty for databases applications in a less than certain world.

31 January 2008 in Soft Computing
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RLRoy Ladner
Roy Ladner
Fred PetryFred Petry
Fred Petry
KGKalyan Moy Gupta
Kalyan Moy Gupta
EWElizabeth Warner
Elizabeth Warner
PMPhilip Moore
Philip Moore
DADavid W. Aha
David W. Aha

28 May 2019 in Journal of Ambient Intelligence and Humanized Computing
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Journal Article
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PEPaul Elmore
Paul Elmore
DADerek Anderson
Derek Anderson
Fred PetryFred Petry
Fred Petry

11 October 2004 in Soft Computing
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Journal Article
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TBT. Beaubouef
T. Beaubouef
Fred PetryFred Petry
Fred Petry