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Computational Models of Complex Systems
Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the readers will have stimulating experiences to pursue research in these directions.
Theories and Simulations of Complex Social Systems
Research into social systems is challenging due to their complex nature. Traditional methods of analysis are often difficult to apply effectively as theories evolve over time. This can be due to a lack of appropriate data, or too much uncertainty. It can also be the result of problems which are not yet understood well enough in the general sense so that they can be classified, and an appropriate solution quickly identified. Simulation is one tool that deals well with these challenges, fits in well with the deductive process, and is useful for testing theory. This field is still relatively new, and much of the work is necessarily innovative, although it builds upon a rich and varied foundation. There are a number of existing modelling paradigms being applied to complex social systems research. Additionally, new methods and measures are being devised through the process of conducting research. We expect that readers will enjoy the collection of high quality research works from new and accomplished researchers.
Societal Conscious Fuzzy Cognitive Models
Dr.Nivetha Martin, Asst. Prof of Mathematics, Arul Anandar College. Dr.S.Jegan Karuppiah, Asst. Prof of Rural Development Science, Arul Anandar College.
Case Studies in Intelligent Computing
Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems. This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful machine learning and AI-based applications across various industries, including: A non-invasive and i...
Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems
In the last decade there has been a phenomenal growth in interest in crime pattern analysis. Geographic information systems are now widely used in urban police agencies throughout industrial nations. With this, scholarly interest in understanding crime patterns has grown considerably. Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems discusses leading research on the use of computer simulation of crime patterns to reveal hidden processes of urban crimes, taking an interdisciplinary approach by combining criminology, computer simulation, and geographic information systems into one comprehensive resource.
Modelling in Healthcare
A model is a simplified representation of a real-world situation used to help answer a specific question. This book provides a look into the world of modelling with the focus on modelling in healthcare.--[from preface]
The Dark Social Capital of Religious Radicals
With the departure of European Muslims to the “Islamic State” and a wave of terrorist attacks in Europe in recent years, the questions of why and how individuals radicalize to Jihadi extremism attracted keen interest. This thesis examines how individuals radicalize by applying a theoretical framework that primarily refers to social capital theory, the economics of religion, and social movement theory. The analysis of the biographical backgrounds, pathways of radicalization, and network connections of more than 1,300 Jihadi extremists from Germany, Austria, and Switzerland shows that radicalization primarily need to be considered as a social process of isolation from former social contact...
Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field.Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.
Social Network Analysis in Predictive Policing
This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-of...
The Oxford Handbook of Environmental Criminology
The study of how the environment, local geography, and physical locations influence crime has a long history that stretches across many research traditions. These include the neighborhood effects approach developed in the 1920s, the criminology of place, and a newer approach that attends to the perception of crime in communities. Aided by new technologies and improved data-reporting in recent decades, research in environmental criminology has developed rapidly within each of these approaches. Yet research in the subfield remains fragmented and competing theories are rarely examined together. The Oxford Handbook of Environmental Criminology takes a unique approach and synthesizes the contribu...
