Advances in machine learning for big data analysis
Singapore: Springer, [2022]
Online
Bibliografie, Sammelwerk, Elektronische Ressource
- 1 online resource (xix, 239 pages) : illustrations (some color), charts.
Ermittle Ausleihstatus...
This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems.
1. Multi-objective ant colony optimization : an updated review of approaches and applications -- 2. Cost-effective detection of cyber physical system attacks -- 3. A prognostic approach to crime analysis -- 4. A counter-based profiling scheme for improving locality through data and reducer placement -- 5. Hybridization of the higher order neural networks with the evolutionary optimization algorithms--an application to financial time series forecasting -- 6. Supply chain management (SCM) : employing various big data and metaheuristic strategies -- 7. Value of random vector functional link neural networks in software development effort estimation -- 8. Hybrid approach to prevent accidents at railway : an assimilation of big data, IoT and cloud -- 9. Hybrid decision tree for machine learning : a big data perspective.
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Advances in machine learning for big data analysis
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Verantwortlichkeitsangabe: | Satchidananda Dehuri, Yen-Wei Chen, editors |
Autor/in / Beteiligte Person: | Dehuri, Satchidananda [editor.] ; Chen, Yen-Wei [editor.] |
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Veröffentlichung: | Singapore: Springer, [2022] |
Medientyp: | Bibliografie, Sammelwerk |
Datenträgertyp: | Elektronische Ressource |
Umfang: | 1 online resource (xix, 239 pages) : illustrations (some color), charts. |
ISBN: | 981-16-8929-6; 981-16-8930-X |
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