Natural computing for unsupervised learning
Xiangtao Li, Ka-Chun Wong, editors (Springer Nature, 2019)
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| This book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, artificial life, quantum computing, DNA computing, and others. The book also includes information on the use of natural computing techniques for unsupervised learning tasks. It features several trending topics, such as big data scalability, wireless network analysis, engineering optimization, social media, and complex network analytics. It shows how these applications have triggered a number of new natural computing techniques to improve the performance of unsupervised learning methods. With this book, the readers can easily capture new advances in this area with systematic understanding of the scope in depth. Readers can rapidly explore new methods and new applications at the junction between natural computing and unsupervised learning. Includes advances on unsupervised learning using natural computing techniquesReports on topics in emerging areas such as evolutionary multi-objective unsupervised learningFeatures natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms |
 Natural Computing for Unsupervised Learning.pdf :: Unduh
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| No. Panggil : | e20509294 |
| Entri tambahan-Nama orang : | |
| Subjek : | |
| Penerbitan : | Switzerland: Springer Nature, 2019 |
| Sumber Pengatalogan: | LibUI eng rda |
| Tipe Konten: | text |
| Tipe Media: | computer |
| Tipe Pembawa: | online resource |
| Deskripsi Fisik: | vi, 273 pages : illustration |
| Tautan: | https://doi.org/10.1007/978-3-319-98566-4 |
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| No. Panggil | No. Barkod | Ketersediaan |
|---|---|---|
| e20509294 | 02-20-587352079 | TERSEDIA |
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| Tidak ada ulasan pada koleksi ini: 20509294 |
