Error Systems: Concepts, Theory and Applications: 275 1st ed. 2020 Edition

Error Systems: Concepts, Theory and Applications: 275 1st ed. 2020 Edition book cover

Error Systems: Concepts, Theory and Applications: 275 1st ed. 2020 Edition

Author(s): Kaizhong Guo (Author), Shiyong Liu (Author)

  • Publisher: Springer
  • Publication Date: 1 Mar. 2021
  • Edition: 1st ed. 2020
  • Language: English
  • Print length: 367 pages
  • ISBN-10: 3030407624
  • ISBN-13: 9783030407629

Book Description

This book offers a new perspective and deeper understanding of complex socioeconomic systems, and explores the laws and mechanisms of erring by revealing the system structure, i.e., the context in which errors are imbedded. It proposes a number of new concepts for the field of systems science concerning the forces affecting e.g. system structure, subsystem structures, and system elements.

Given its scope, it offers an excellent reference book for researchers and other readers in the fields of systems science, management science, mathematics, fuzzy logic and sets, symbolic logic, philosophy, etc. The book can also benefit researchers and practitioners in artificial intelligence and machine learning, as various erring patterns can be identified by training intelligent machines with big data (i.e., error cases and their logic), helping to prevent or eliminate errors in a cost-effective manner.

Editorial Reviews

From the Back Cover

This book offers a new perspective and deeper understanding of complex socioeconomic systems, and explores the laws and mechanisms of erring by revealing the system structure, i.e., the context in which errors are imbedded. It proposes a number of new concepts for the field of systems science concerning the forces affecting e.g. system structure, subsystem structures, and system elements.

Given its scope, it offers an excellent reference book for researchers and other readers in the fields of systems science, management science, mathematics, fuzzy logic and sets, symbolic logic, philosophy, etc. The book can also benefit researchers and practitioners in artificial intelligence and machine learning, as various erring patterns can be identified by training intelligent machines with big data (i.e., error cases and their logic), helping to prevent or eliminate errors in a cost-effective manner.

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