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Crime Linkage and Psychological Profiling of Offenders Under Intuitionistic Fuzzy Environment Using a Novel Resemblance Measure by Palash Dutta; Abhilash Kangsha Banik is a Computer Science article available to read on EtoBox.

What is Crime Linkage and Psychological Profiling of Offenders Under Intuitionistic Fuzzy Environment Using a Novel Resemblance Measure about?

Crime is a significant issue in society, with the causes of crime needing more attention and action from social, governmental, and judicial entities. Investigating crimes can be challenging due to uncertainties and unreliable evidence. Crime linkage helps investigators identify and solve crimes committed by the same individuals or groups. Fuzzy sets and intuitionistic fuzzy sets have been helpful in decision-making problems related to crime linkage due to the uncertainty involved. Similarity measures are essential in decision-making problems, but the existing measures must be revised when dealing with three or more intuitionistic fuzzy sets. The proposed resemblance measure based on intuitionistic fuzzy sets can find similarities between more than two sets and be used in the crime linkage. The proposed measure's superiority is demonstrated through examples and applied to crime linkage through case studies. A methodology for the psychological profiling of offenders is also presented through case studies. These proposed methods can help law enforcement solve decision-making problems related to crime linkage and psychological profiling.

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Author

Palash Dutta; Abhilash Kangsha Banik

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)