Overview
- Offers a comprehensive introduction to the Topological Weighed Centroid approach
- Covers applications in the analysis of geographical dynamics
- Discusses topics related to the semantic dimension of space and semantic TWC applications
Part of the book series: Studies in Computational Intelligence (SCI, volume 1095)
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Table of contents (7 chapters)
Keywords
About this book
This book introduces the Topological Weighed Centroid approach and describes some applications in the study of the dynamics of various spatial phenomena with a special emphasis on the spatial analysis of the relationship, influence, and dynamics of geographical phenomena. Offering a comprehensive introduction to the theory and illustrative examples from various kinds of geographical data, this book also takes an in-depth look at more complex case studies, such as the applications of the topological weighed centroid approach in the study of epidemic patterns, cultural processes, criminality, and environmental phenomena.
Authors and Affiliations
About the authors
Masoud Asadi-Zeydabadi serves as professor in the Department of Physics, University of Colorado Denver. Masoud Asadi received a Ph.D. in physics from University of Colorado Boulder. His research interests include nonlinear dynamics and chaos, physics education, biological modeling, and medical physics.
Marco Breda is currently the director of the Advanced Analytics and AI in the division of Data and Analytics Center of Excellence at Engineering Ingegneria Informatica. He works with machine learning paradigms for designing and building complex analytical systems for public and private industrial companies in various ICT sectors. He has worked with various IT companies including Ericsson Telecamunicazione’s research division and TIM gathering more than 20 years’ experience in data warehousing, business intelligence, and data mining projects. He is also an associate researcher at the Semeion Research Center in Rome, Italy, where he conducts basic research in artificialintelligence. He has published over 30 papers and teaches data warehousing and advanced analytics at the “Enrico della Valle” School since 2010. He received an M.Sc. in electronic engineering from the “Sapienza” University of Rome in 1989.
Massimo Buscema is the director of Semeion Research Center in Rome, Italy, and is currently a full professor adjoint at the Department of Mathematical and Statistical Sciences, University of Colorado (Denver, USA). He has published more than 300 scientific papers in the field of AI, about 8 scientific books, and 28 international patents. Massimo does research in algorithms, artificial intelligence, and artificial neural networks. His current projects include EEG in autism diagnosis, geographic profiling, artificial neural networks working with many data sets simultaneously, deep learning, and data matrix theory.
Francesca Della Torre is a research associate at the Semeion Research Center in Rome, Italy. She receivedher Master of Science in mathematics from the University of Rome “Tor Vergata” in 2016. Her skills and expertise are in the areas of business intelligence, data science, advanced machine learning, deep learning, computer vision, evolutionary algorithms, artificial intelligence, unsupervised learning, and their respective applications.
Weldon Lodwick is a professor in the Department of Mathematical and Statistical Sciences, University of Colorado Denver. His areas of expertise include computational geographical information systems, uncertainty theory, fuzzy set theory, optimization, and applications especially in the areas of medicine.
Giulia Massini earned a Laurea in Sociology, University of Rome, “La Sapienza,” in 1978.
She was one of the founding members and deputy director of Semeion Research Center in Rome, Italy. She has been working as a computer programmer and data scientist, contributing to several publications, both theoretical and applicative. Her research focuses on graph theory, creation of new algorithms in neural networks, and adaptive artificial systems.
Francis Newman is a professor emeritus at University of Colorado Denver and an adjoint associate professor at the department of Mathematical and Statistical Sciences at the same university. He served as a head radiation physicist at the University of Colorado Denver Anschutz Medical Campus (University of Colorado Hospital). His skills and expertise are in the areas of radiation dosimetry, radiation therapy physics, radiation oncology, medical radiation physics, radiotherapy physics, radiotherapy, dosimetry, IMRT, artificial neural networks, and optimization especially applied to medicine.
Riccardo Petritoli is an associated researcher at Semeion Research Center in Rome, Italy. With over 20 years of experience in machine learning and computer intelligence focused on the design, implementation, and application of analytic adaptive systems, he is also currently serving as a data scientist and customer engagement manager in an international consulting firm. His areas of expertise include predictive and forecasting model design, intelligent automation, strategic planning for business process optimization, marketing, and operational risk management.
Bibliographic Information
Book Title: The Topological Weighted Centroid: A New Vision of Geographic Profiling
Book Subtitle: Theory and Applications
Authors: Massimo Buscema, Masoud Asadi-Zeydabadi, Giulia Massini, Weldon A. Lodwick, Marco Breda, Riccardo Petritoli, Francis Newman, … Francesca Della Torre
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-031-28901-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-28900-2Published: 14 July 2023
Softcover ISBN: 978-3-031-28903-3Due: 14 August 2023
eBook ISBN: 978-3-031-28901-9Published: 13 July 2023
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: IX, 169
Number of Illustrations: 7 b/w illustrations, 135 illustrations in colour
Topics: Computational Intelligence, Computer Applications, Geography, general, Data Mining and Knowledge Discovery