Ebook: Intelligent Data Mining in Law Enforcement Analytics: New Neural Networks Applied to Real Problems

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.

---

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.

---

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.

Content:
Front Matter....Pages i-xviii
Introduction to Artificial Networks and Law Enforcement Analytics....Pages 1-9
Law Enforcement and Artificial Intelligence....Pages 11-16
The General Philosophy of Artificial Adaptive Systems....Pages 17-30
A Brief Introduction to Evolutionary Algorithms and the Genetic Doping Algorithm....Pages 31-49
Artificial Adaptive Systems in Data Visualization: Proactive Data....Pages 51-88
The Metropolitan Police Service Central Drug-Trafficking Database: Evidence of Need....Pages 89-117
Supervised Artificial Neural Networks: Backpropagation Neural Networks....Pages 119-135
Preprocessing Tools for Nonlinear Datasets....Pages 137-155
Metaclassifiers....Pages 157-165
Auto-Identification of a Drug Seller Utilizing a Specialized Supervised Neural Network....Pages 167-175
Visualization and Clustering of Self-Organizing Maps....Pages 177-192
Self-Organizing Maps: Identifying Nonlinear Relationships in Massive Drug Enforcement Databases....Pages 193-214
Theory of Constraint Satisfaction Neural Networks....Pages 215-229
Application of the Constraint Satisfaction Network....Pages 231-313
Auto-Contractive Maps, H Function, and the Maximally Regular Graph: A New Methodology for Data Mining....Pages 315-381
Analysis of a Complex Dataset Using the Combined MST and Auto-Contractive Map....Pages 383-398
Auto-Contractive Maps and Minimal Spanning Tree: Organization of Complex Datasets on Criminal Behavior to Aid in the Deduction of Network Connectivity....Pages 399-413
Data Mining Using Nonlinear Auto-Associative Artificial Neural Networks: The Arrestee Dataset....Pages 415-479
Artificial Adaptive System for Parallel Querying of Multiple Databases....Pages 481-511
Back Matter....Pages 513-516

---

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.

Content:
Front Matter....Pages i-xviii
Introduction to Artificial Networks and Law Enforcement Analytics....Pages 1-9
Law Enforcement and Artificial Intelligence....Pages 11-16
The General Philosophy of Artificial Adaptive Systems....Pages 17-30
A Brief Introduction to Evolutionary Algorithms and the Genetic Doping Algorithm....Pages 31-49
Artificial Adaptive Systems in Data Visualization: Proactive Data....Pages 51-88
The Metropolitan Police Service Central Drug-Trafficking Database: Evidence of Need....Pages 89-117
Supervised Artificial Neural Networks: Backpropagation Neural Networks....Pages 119-135
Preprocessing Tools for Nonlinear Datasets....Pages 137-155
Metaclassifiers....Pages 157-165
Auto-Identification of a Drug Seller Utilizing a Specialized Supervised Neural Network....Pages 167-175
Visualization and Clustering of Self-Organizing Maps....Pages 177-192
Self-Organizing Maps: Identifying Nonlinear Relationships in Massive Drug Enforcement Databases....Pages 193-214
Theory of Constraint Satisfaction Neural Networks....Pages 215-229
Application of the Constraint Satisfaction Network....Pages 231-313
Auto-Contractive Maps, H Function, and the Maximally Regular Graph: A New Methodology for Data Mining....Pages 315-381
Analysis of a Complex Dataset Using the Combined MST and Auto-Contractive Map....Pages 383-398
Auto-Contractive Maps and Minimal Spanning Tree: Organization of Complex Datasets on Criminal Behavior to Aid in the Deduction of Network Connectivity....Pages 399-413
Data Mining Using Nonlinear Auto-Associative Artificial Neural Networks: The Arrestee Dataset....Pages 415-479
Artificial Adaptive System for Parallel Querying of Multiple Databases....Pages 481-511
Back Matter....Pages 513-516
....