Intelligent Data Analytics for Terror Threat Prediction: Architectures,Methodologies,Techniques,and Applications


Intelligent Data Analytics for Terror Threat Prediction: Architectures,Methodologies,Techniques,and Applications
by Subhendu Kumar Pani,Sanjay Kumar Singh,Lalit Garg,Ram Bilas Pachori,Xiaobo Zhang
Publisher Finelybook 出版社: Wiley-Scrivener; 1st edition (February 9,2021)
Language 语言: English
pages 页数: 352 pages
ISBN-10 书号: 1119711096
ISBN-13 书号: 9781119711094


Book Description
Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science,bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis.
This book provides innovative insights that will help obtain interventions to undertake emerging dynamic scenarios of criminal activities. Furthermore,it presents emerging issues,challenges and management strategies in public safety and crime control development across various domains. The book will play a vital role in improvising human life to a great extent. Researchers and practitioners working in the fields of data mining,machine learning and artificial intelligence will greatly benefit from this book,which will be a good addition to the state-of-the-art approaches collected for intelligent data analytics. It will also be very beneficial for those who are new to the field and need to quickly become acquainted with the best performing methods. With this book they will be able to compare different approaches and carry forward their research in the most important areas of this field,which has a direct impact on the betterment of human life by 作者: maintaining the security of our society. No other book is currently on the market which provides such a good collection of state-of-the-art methods for intelligent data analytics-based models for terror threat prediction,as intelligent data analytics is a newly emerging field and research in data mining and machine learning is still in the early stage of development.

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