Big Data and Information Theory (eBook, ePUB)

Redaktion: Xu, Jiuping; Li, Zongmin; Ahmed, Syed Ejaz

• Format: ePub

Produktbeschreibung

This book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 128
• Erscheinungstermin: 1. Juni 2022
• Englisch
• ISBN-13: 9781000591781
• Artikelnr.: 63448918

Inhaltsangabe

Preface 1. Engineering management: new advances and three open questions 2. Bayes and big data: the consensus Monte Carlo algorithm 3. Measurement and analysis of quality of life related to environmental hazards: the methodology illustrated by recent epidemiological studies 4. Big data analytics: integrating penalty strategies 5. Seeking relationships in big data: a Bayesian perspective 6. Designing a data-driven leagile sustainable closed-loop supply chain network 7. Exploring capability maturity models and relevant practices as solutions addressing information technology service offshoring project issues 8. The evolution and governance of online rumors during the public health emergency: taking COVID-19 pandemic related rumors as an example 9. An empirical study of data warehouse implementation effectiveness 10. Developing a preliminary cost estimation model for tall buildings based on machine learning 11. A framework for managing uncertainty in information system project selection: an intelligent fuzzy approach