Network Science Models for Data Analytics Automation: Theories and Applications

This book provides a comprehensive introduction to network science and its applications in data analytics, bridging the gap between theory and practice. It is suitable for engineers, researchers, and managers, and advanced undergraduate and graduate students in mathematics, statistics, engineering, business, public health, and social science.

Format: Hardback
Length: 122 pages
Publication date: 22 February 2022
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into the realm of network science, providing a comprehensive understanding of its applications in data analytics for critical infrastructures, engineered systems, and knowledge acquisition. Spanning multiple chapters, it intricately outlines the step-by-step processes through which network science empowers and automates data analytics, offering practical examples along the way. Beyond dissecting modeling techniques and analytical outcomes, the book delves into the intrinsic development of these models and analyses, fostering a deep understanding of the underlying principles. By bridging the gap between theory and practice, this unique approach equips readers with managerial and problem-solving skills, making it invaluable for engineers, researchers, and managers alike.

Advanced undergraduate students and graduate students in mathematics, statistics, engineering, business, public health, and social science will find this book an indispensable resource as a one-semester textbook or a reference book. For readers with a more focused interest in applications, Chapter 1 can be skipped, allowing for a seamless exploration of the remaining chapters.

Weight: 366g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030964696
Edition number: 1st ed. 2022