The increasing frequency of crimes against wives worldwide underscores the necessary to identify and implement effective measures to check such occurrence. In order to protect women from cheat, it is necessary to analyze misdeed trends systematically to determine patterns that can serve as valuable precautionary measures. In existing studies focused on crime study, conventional hard assembling techniques are commonly working to assess the prevalence of criminal endeavors in specific regions. However, these grouping methods, grounded in fresh set theory, encounter challenges in handling biased membership, making it troublesome to identify regions presenting partial affiliation accompanying multiple clusters characterized by variable crime intensities. Recognizing the constraints guide hard clustering techniques, we aim to engage a fuzzy grouping approach to a dataset related to crimes against daughters, with the objective of elucidating important patterns within the data.
Author(s) Details:
Samarjit Das,
CSE,
The Assam Royal Global University, Guwahati, India.
Atowar
Ul Islam,
Department
of Computer Science, University of Science & Technology, Ri-Bhoi,
Meghalaya, India.
Anupam Das,
CSE, The Assam Royal Global University, Guwahati, India.
Please see the link here: https://stm.bookpi.org/RATMCS-V6/article/view/12522
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