
Advances in Complex Decision Making
Using Machine Learning and Tools for Service-Oriented Computing
- 112 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Advances in Complex Decision Making
Using Machine Learning and Tools for Service-Oriented Computing
About this book
The rapidly evolving business and technology landscape demands sophisticated decision-making tools to stay ahead of the curve. Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing is a cutting-edge technical guide exploring the latest decision-making technology advancements. This book provides a comprehensive overview of machine learning algorithms and examines their applications in complex decision-making systems in a service-oriented framework.
The authors also delve into service-oriented computing and how it can be used to build complex systems that support decision making. Many real-world examples are discussed in this book to provide a practical insight into how discussed techniques can be applied in various domains, including distributed computing, cloud computing, IoT and other online platforms.
For researchers, students, data scientists and technical practitioners, this book offers a deep dive into the current developments of machine learning algorithms and their applications in service-oriented computing. This book discusses various topics, including Fuzzy Decisions, ELICIT, OWA aggregation, Directed Acyclic Graph, RNN, LSTM, GRU, Type-2 Fuzzy Decision, Evidential Reasoning algorithm and robust optimisation algorithms. This book is essential for anyone interested in the intersection of machine learning and service computing in complex decision-making systems.
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Information
Table of contents
- Cover Page
- Half Title page
- Title Page
- Copyright Page
- Contents
- Preface
- Acknowledgements
- About the Editors
- List of Contributors
- 1 Application of Choquet–OWA Aggregation Operator to Fuse ELICIT Information
- 2 GPipe: Using Adaptive Directed Acyclic Graphs to Run Data and Feature Pipelines with on-the-fly Transformations
- 3 Building an ESG Decision-Making System: Challenges and Research Directions
- 4 Analysing Trust, Security and Cost of Cloud Consumer’s Reviews using RNN, LSTM, and GRU
- 5 Interval Type-2 Fuzzy Decision Analysis Framework Based on Online Textual Reviews
- 6 Robust Comprehensive Minimum Cost Consensus Model for Multi-Criteria Group Decision Making: Application in IoT Platform Selection
- Index
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