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Optimization, learning, and control for interdependent complex networks. (English) Zbl 1435.68017

Advances in Intelligent Systems and Computing 1123. Cham: Springer (ISBN 978-3-030-34093-3/hbk; 978-3-030-34094-0/ebook). x, 304 p. (2020).
Publisher’s description: This book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role in smart energy systems, intelligent transportation networks, and smart cities. This book paves the way for researchers working on optimization, learning, and control spread over the fields of computer science, operation research, and electrical engineering. This book covers optimization algorithms for large-scale problems from theoretical foundations to real world applications, learning-based methods to enable intelligence in future smart cities, and control techniques to deal with the optimal and robust operation of complex systems. It further introduces novel algorithms for data analytics in large-scale interdependent networks.
\(\bullet\) Specifies the importance of efficient theoretical methods in dealing with problems in the context of interdependent networks
\(\bullet\) Provides a comprehensive investigation of recently developed algorithms for largescale networks
\(\bullet\) Presents basics and mathematical foundations needed to analyze and address the interdependent complex networks
The articles of this volume will not be indexed individually.

MSC:

68-06 Proceedings, conferences, collections, etc. pertaining to computer science
68Txx Artificial intelligence
90B10 Deterministic network models in operations research
90C35 Programming involving graphs or networks
93B70 Networked control
93C83 Control/observation systems involving computers (process control, etc.)
00B15 Collections of articles of miscellaneous specific interest
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