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

Massimo Buscema and William J. Tastle, editors
Publisher: 
Springer
Publication Date: 
2013
Number of Pages: 
516
Format: 
Hardcover
Price: 
229.00
ISBN: 
9789400749139
Category: 
Anthology
We do not plan to review this book.

Dedication.- Preface.- Chapter 1. Introduction to Artificial Networks and Law Enforcement Analytics; William J. Tastle.- Chapter 2. Law Enforcement and Artificial Intelligence; Massimo Buscema.- Chapter 3. The General Philosophy of Artificial Adaptive Systems; Massimo Buscema.- Chapter 4. A Brief Introduction to Evolutionary Algorithms and the Genetic Doping Algorithm; M. Buscema, M. Capriotti.- Chapter 5. Artificial Adaptive Systems in Data Visualization: Pro-Active data; Massimo Buscema.- Chapter 6. The Metropolitan Police Service Central Drug Trafficking Database: Evidence of Need; Geoffrey Monaghan and Stefano Terzi.- Chapter 7. Supervised Artificial neural Networks: Back Propagation Neural Networks; Massimo Buscema.- Chapter 8. Pre-Processing Tools for Non-Linear Data Sets; Massimo Buscema, Alessandra Mancini and Marco Breda.- Chapter 9. Metaclassifiers; Massimo Buscema, Stefano Terzi.- Chapter 10. Auto Identification of a Drug Seller Utilizing a Specialized Supervised Neural Network; Massimo Buscema and Marco Intraligi.- Chapter 11. Visualization and Clustering of Self-Organizing Maps; Giulia Massini.- Chapter 12. Self-Organizing Maps: Identifying Non-Linear Relationships in Massive Drug Enforcement Databases; Guila Massini.- Chapter 13. Theory of Constraint Satisfaction Neural Networks; Massimo Buscema.- Chapter 14. Application of the Constraint Satisfaction Network; Marco Intraligi and Massimo Buscema.- Chapter 15. Auto-Contractive Maps, h Function and the Maximally regular Graph: A new methodology for data mining; Massimo Buscema.- Chapter 16. Analysis of a Complex Dataset Using the Combined MST and Auto Contractive Map; Giovanni Pieri.- Chapter 17. Auto Contractive Mapsand Minimal Spanning tree: Organization of Complex datasets on criminal behavior to aid in the deduction of network connectivity; Giula Massini and Massimo Buscema.- Chapter 18. Data Mining Using Non-linear Auto Associative Artificial Neural Networks: The Arrestee Dataset; Massimo Buscema.- Chapter 19. Artificial Adaptive System for Parallel Querying of Multiple Databases; Massimo Buscema.-

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