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Titolo: |
Computational intelligence for multimedia big data on the cloud with engineering applications / / edited by Arun Kumar Sangaiah, Michael Sheng, Zhiyong Zhang
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Pubblicazione: | London, United Kingdom : , : Academic Press, an imprint of Elsevier, , [2018] |
©2018 | |
Edizione: | First edition. |
Descrizione fisica: | 1 online resource (364 pages) : illustrations |
Disciplina: | 006.3 |
Soggetto topico: | Computational intelligence |
Cloud computing | |
Big data | |
Persona (resp. second.): | SangaiahArun Kumar <1981-> |
ShengQuan Z. | |
ZhangZhiyong | |
Sommario/riassunto: | Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. |
Titolo autorizzato: | Computational intelligence for multimedia big data on the cloud with engineering applications ![]() |
ISBN: | 0-12-813327-9 |
0-12-813314-7 | |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910583315803321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |