Data science in engineering and management : applications, new developments, and future trends

著者

    • Polkowski, Zdzislaw
    • Mishra, Sambit Kumar
    • Vasilev, Julian

書誌事項

Data science in engineering and management : applications, new developments, and future trends

edited by Zdzislaw Polkowski, Sambit Kumar Mishra, Julian Vasilev

CRC Press, 2022

  • : hbk

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内容説明・目次

内容説明

Gets the reader up to date with an introduction to the concept of data science, its reasons and origin Focused on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis Provides an overview of recent developments and applications on data linked to engineering and management perspectives Covers how data scientists, analysts, and program managers that are interested in productivity and improving their business can do so by incorporating a data science workflow effectively Presents recent trends, highlights future developments, along with discussing problems and offering suggested solutions

目次

1. Concepts for Effective Mobile Devices Management in Enterprise Environment. 2. Prioritization of Informational Factors and Query Intensification Using Meta-heuristic Approach. 3. Estimation and Potential Evaluation of Data Linked to Virtual Machines Using Computational Approach. 4. Potential Applications of Blockchain Technology in Construction Sector. 5. Artificial Neural Networks Applications in Social Media Activities Impact on Depression During the COVID-19 Pandemic. 6. Analysis of CCT through ANFIS for Grid Connected SPV System. 7. Frequency Analysis of Human Brain Response to Sudarshan Kriya Meditation. 8. Coordinated Control Action Between DFIG-Grid Interconnected System Using PI Based SVM Controller. 9. Acceptance of New School in Semi-Urban Areas of India: An Application of Data Mining. 10. Two- Phase Natural Convection of Dusty Fluid Boundary Layer Flow Over a Vertical Plate. 11. An Interactive Injection Mold Design with CAE and Moldflow Analysis for Plastic Components. 12. Study of Collaborative Filtering based Personalized Recommendation Quality, Relevance and Timing Effect on Users' Decision to Purchase.

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