Intelligent data mining in law enforcement analytics : new neural networks applied to real problems /
Massimo Buscema, William J. Tastle, editors.
- xviii, 516 pages : illustrations ; 24 cm
Includes bibliographical references and index.
Introduction to artificial networks and law enforcement analytics -- Law enforcement and artificial intelligence -- The general philosophy of artificial adaptive systems -- A brief introduction to evolutionary algorithms and the genetic doping algorithm -- Artificial adaptive systems in data visualization : proactive data -- The Metropolitan police service central drug-trafficking database : evidence of need -- Supervised artificial neural networks : backpropagation neural networks -- Preprocessing tools for nonlinear datasets -- Metaclassifiers -- Auto-identification of a drug seller utilizing a specialized supervised neural network -- Visualization and clustering of self-organizing maps -- Self-organizing maps : identifying nonlinear relationships in massive drug enforcement databases -- Theory of constraint satisfaction neural networks -- Application of the constraint satisfaction network -- Auto-contractive maps, H function, and the maximally regular graph : a new methodology for data mining -- Analysis of a complex dataset using the combined MST and auto-contractive map -- Auto-contractive maps and minimal spanning tree : organization of complex datasets on criminal behavior to aid in the deduction of network connectivity -- Data mining using nonlinear auto-associative artificial neural networks : the arrestee dataset -- Artificial adaptive system for parallel querying of multiple databases.
This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.--
9789400749139 (alk. paper) 9400749139 (alk. paper) 9789400749146 (ebk.)
2012953015
016196466 Uk
Data mining in law enforcement.
Social sciences--Methodology.
Neural networks (Computer science)
Data mining in law enforcement.
Neural networks (Computer science)
Social sciences--Methodology.
QA76.9.D343 / I5744 2013
006.3/2
Includes bibliographical references and index.
Introduction to artificial networks and law enforcement analytics -- Law enforcement and artificial intelligence -- The general philosophy of artificial adaptive systems -- A brief introduction to evolutionary algorithms and the genetic doping algorithm -- Artificial adaptive systems in data visualization : proactive data -- The Metropolitan police service central drug-trafficking database : evidence of need -- Supervised artificial neural networks : backpropagation neural networks -- Preprocessing tools for nonlinear datasets -- Metaclassifiers -- Auto-identification of a drug seller utilizing a specialized supervised neural network -- Visualization and clustering of self-organizing maps -- Self-organizing maps : identifying nonlinear relationships in massive drug enforcement databases -- Theory of constraint satisfaction neural networks -- Application of the constraint satisfaction network -- Auto-contractive maps, H function, and the maximally regular graph : a new methodology for data mining -- Analysis of a complex dataset using the combined MST and auto-contractive map -- Auto-contractive maps and minimal spanning tree : organization of complex datasets on criminal behavior to aid in the deduction of network connectivity -- Data mining using nonlinear auto-associative artificial neural networks : the arrestee dataset -- Artificial adaptive system for parallel querying of multiple databases.
This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.--
9789400749139 (alk. paper) 9400749139 (alk. paper) 9789400749146 (ebk.)
2012953015
016196466 Uk
Data mining in law enforcement.
Social sciences--Methodology.
Neural networks (Computer science)
Data mining in law enforcement.
Neural networks (Computer science)
Social sciences--Methodology.
QA76.9.D343 / I5744 2013
006.3/2