Uncertainty, Computational Techniques and Decision Intelligence

Aim & scope

Topics include:

Intelligent decision support systems; Uncertainty management in smart decision support systems; Uncertain auto-learning systems; Soft computing in decision making; Dynamical systems under uncertainty; Biological data science and uncertainty; Machine reasoning; Logical rule-based systems; Structural reliability and risk assessment.

Key features:

• Introduces novel approaches, solutions, and state-of-the-art tools for decision-making related problems across a wide range of application fields such as engineering, healthcare, biology, environmental science, and management science

• Investigates new techniques in the field of decision intelligence for handling, processing, and deciding on the use of multi-type large data sets

• Offers researchers from a wide range of fields a unique opportunity to gain insights into the processes of exploiting and steering systems, as well as automating and optimizing their decision-making processes, where uncertainty is inherent

• Covers recent breakthroughs in computational intelligence, mathematical foundations and techniques, and integration with learning and pattern recognition methods and their applications

New Volume Proposals:

• Volumes can be Edited, Multi-Authored, or Authored Monographs

• New volume proposals should:

  • Include a well-structured Table of Contents

  • Include a list of confirmed or tentative, geographically distributed, authors (for Edited volumes)

Indexing: All published volumes in this book series are submitted for indexing in:

• Scopus

• EI Indexing / Compendex

• Book Citation Index

• Google Scholar

Audience

The primary audience of the series includes upper-division undergraduate and postgraduate students, and researchers in the field of applied mathematics, computer science, and industrial engineering. Decision-makers, R&D managers, and especially those in IT-based companies, can also benefit from this book series.

Publish a book with Elsevier

• Information for Authors

• Propose a book 打開新的分頁／視窗

• Contact an Acquisitions Editor

Series Volumes

• Computational Intelligence Techniques for Sustainable Supply Chain Management 打開新的分頁／視窗

• Artificial Intelligence Methods for Optimization of the Software Testing Process 打開新的分頁／視窗

• Uncertainty in Data Envelopment Analysis 打開新的分頁／視窗

• Handbook of Metaheuristic Algorithms 打開新的分頁／視窗

• Reachable Sets of Dynamic Systems 打開新的分頁／視窗

• Decision-Making Models A Perspective of Fuzzy Logic and Machine Learning 打開新的分頁／視窗