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Handbook of research on smart technology models for business and industry / J. Joshua Thomas, Ugo Fiore, Gilberto Perez Lechuga, Valeriy Kharchenko and Pandian Vasant.

EBSCOhost Academic eBook Collection (North America) Available online

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Format:
Book
Contributor:
Thomas, J. Joshua, 1973- editor.
Fiore, Ugo, editor.
Lechuga, Gilberto Perez, editor.
Kharchenko, Valeriy, 1938- editor.
Vasant, Pandian, editor.
Language:
English
Subjects (All):
Automation.
Artificial intelligence--Industrial applications.
Artificial intelligence.
Big data.
Business--Data processing.
Business.
Physical Description:
29 PDFs (491 pages)
Place of Publication:
United States of America : IGI Global, 2020.
System Details:
Mode of access: World Wide Web.
Summary:
"This book discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies"-- Provided by publisher.
Contents:
Chapter 1. Decentralized cryptocurrency security and financial implications: the bitcoin paradigm
Chapter 2. Technique of plant electrical stimulation by weak electric currents
Chapter 3. IoT limitations and concerns relative to 5g architecture
Chapter 4. Calculation of receipt of renewable energy resources and operation modes of power plants
Chapter 5. Cooperative caching in wireless mesh networks
Chapter 6. Smart computerized essay scoring using deep neural networks for universities and institutions
Chapter 7. Application of machine learning algorithms in stock market prediction: a comparative analysis
Chapter 8. Wind energy perspectives in Myanmar
Chapter 9. Improved distributed energy systems based on the end-user consumption profile: a review on how consumers can drive the energy transition
Chapter 10. Selection of an information source and methodology for calculating solar resources of the Kyrgyz Republic
Chapter 11. Smart tourist destination management using demand forecasting techniques: using big data for destination demand forecasting as part of a destination management system
Chapter 12. Development of DNN model for predicting surge pressure gradient during tripping operations
Chapter 13. A cloud computing-based model for wildlife conservation and health care improvement in endangered wild life animals
Chapter 14. Modelling and forecasting portfolio inflows: a comparative study of support vector regression, artificial neural networks, and structural VAR models
Chapter 15. Meta-heuristic approaches for the optimization of hydropower energy: a review
Chapter 16. Wireless technology of electric power transmission using non-metal conductive media
Chapter 17. Development of Box Behnken design to predict the optimum operating condition of rectangular sheet membrane to increase permeate flux
Chapter 18. Computational intelligence in the reversible data-hiding processes using radon transform
Chapter 19. Genetic algorithm and particle swarm optimization techniques in supply chain design problems: a Survey.
Notes:
Description based on print version record.
Includes index.
Includes bibliographical references and index.
ISBN:
1-7998-3646-0
OCLC:
1140373302

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