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Digital
Glance at the Silk Road Disaster Risk
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ISBN: 9789811955839 9789811955822 9789811955846 9789811955853 Year: 2022 Publisher: Singapore Springer Nature

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Abstract

This book vividly shows the fostering environment, activity characteristics, distribution pattern, economic losses, casualties, disaster risks and management of earthquakes, mass movement, drought, floods, and marine disasters in the Silk Road region. It develops a multi-scale and multi-disaster risk assessment method to better assess and understand the Silk Road disaster risk. A multi-level collaborative risk management model has been proposed for transboundary disasters, and it also shares case studies on major disaster risk management. The book makes a major step forward to increase the understanding of the disaster risk of the Silk Road region. It presents a holistic understanding of the natural hazards and their induced disaster risks and is a valuable read for scholars, stakeholders and practitioners in the DRR community.


Digital
Computational Intelligence for Network Structure Analytics
Authors: --- --- --- ---
ISBN: 9789811045585 Year: 2017 Publisher: Singapore Springer Singapore, Imprint: Springer

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This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications. As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment. Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.

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