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The rapidly evolving business and technology landscape demands
sophisticated decision-making tools to stay ahead of the curve. The
book Advances in Complex Decision Making: Using Machine Learning
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 application 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. The 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.
The rapidly evolving business and technology landscape demands
sophisticated decision-making tools to stay ahead of the curve. The
book Advances in Complex Decision Making: Using Machine Learning
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 application 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. The 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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Enterprise Applications, Markets and Services in the Finance Industry - 11th International Workshop, FinanceCom 2022, Twente, The Netherlands, August 23–24, 2022, Revised Selected Papers (1st ed. 2023)
Jos van Hillegersberg, Jörg Osterrieder, Fethi Rabhi, Abhishta Abhishta, Vijay Marisetty, …
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R1,638
Discovery Miles 16 380
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Ships in 10 - 15 working days
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This book constitutes revised selected papers from the 11th
International Workshop on Enterprise Applications, Markets and
Services in the Finance Industry, FinanceCom 2022, held in Twente,
The Netherlands, in August 2022. The 8 full papers presented in
this volume were carefully reviewed and selected from a total of 25
submissions. They deal with the adoption of innovative technologies
in the financial services industry. The conference features four
main themes: networks and business models, financial markets, IT
and implementations, and new emerging digital and virtual financial
markets.
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