Title
Crime activities prediction using hybridization of firefly optimization technique and fuzzy cognitive map neural networks
Abstract
In the developing technology, crime reduction is one of the major and complex processes due to the various techniques and minimum amount of crime-related data. The traditional method is difficult to identify the crime activities with effective manner due to the minimum data. So, this paper introduces the novel big data and soft computing techniques for recognizing the crime activities with effective manner. Initially, the crime activities-related data have been collected from the various resources present in the big data. From the collected data, the inconsistent data and missing values are eliminated by applying the incremental mean normalization method. After that, the similar crime data have been clustered with the help of the fireflies-based fuzzy cognitive map neural networks which help to predict the crime activity-related features with effective manner. Finally, the prediction process is done by using the enhanced associative neural networks approach. The efficiency of the system is evaluated with the help of the experimental results and discussions in terms of the precision, recall, accuracy.
Year
DOI
Venue
2019
10.1007/s00521-018-3561-7
Neural Computing and Applications
Keywords
Field
DocType
Crime analysis, Firefly algorithm, Neural networks, Fuzzy clustering
Fuzzy clustering,Fuzzy cognitive map,Firefly algorithm,Artificial intelligence,Missing data,Soft computing,Artificial neural network,Big data,Machine learning,Mathematics,Crime analysis
Journal
Volume
Issue
ISSN
31.0
SP5.0
1433-3058
Citations 
PageRank 
References 
1
0.35
3
Authors
2
Name
Order
Citations
PageRank
Torki A. Altameem1324.64
Mohammed Amoon2154.67