Data And Decision Sciences Recent Advances And Applications


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Data and Decision Sciences - Recent Advances and Applications


Data and Decision Sciences - Recent Advances and Applications

Author:

language: en

Publisher: BoD – Books on Demand

Release Date: 2023-10-25


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This book provides an overview of Data and Decision Sciences (DDS) and recent advances and applications in space-based systems and business, medical, and agriculture processes, decision optimization modeling, and cognitive decision-making. Written by experts, this volume is organized into four sections and seven chapters. It is a valuable resource for educators, engineers, scientists, and researchers in the field of DDS.

Advances in Decision Science and Management


Advances in Decision Science and Management

Author: Taosheng Wang

language: en

Publisher: Springer Nature

Release Date: 2021-07-26


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This book discusses an emerging area in computer science, IT, and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the Third International Conference on Decision Science and Management 2021 (ICDSM 2021), held at Hang Seng University of Hong Kong in China.

Application of Decision Science in Business and Management


Application of Decision Science in Business and Management

Author: Fausto Pedro García Márquez

language: en

Publisher: BoD – Books on Demand

Release Date: 2020-03-04


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Application of Decision Science in Business and Management is a book where each chapter has been contributed by a different author(s). The chapters introduce and demonstrate a decision-making theory to practice case studies. It demonstrates key results for each sector with diverse real-world case studies. Theory is accompanied by relevant analysis techniques, with a progressive approach building from simple theory to complex and dynamic decisions with multiple data points, including big data, lot of data, etc. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support analysis of multi-criteria decision-making problems with defined constraints and requirements. The book provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of decision making. It is complementary to other sub-disciplines such as economics, finance, marketing, decision and risk analysis, etc.