Recurrent Neural Networks and Soft Computing
dc.contributor.editor | ElHefnawi, Mahmoud | |
dc.contributor.editor | Mysara, Mohamed | |
dc.date.accessioned | 2021-04-20T15:29:47Z | |
dc.date.available | 2021-04-20T15:29:47Z | |
dc.date.issued | 2012 | |
dc.identifier | ONIX_20210420_9789535104094_1295 | |
dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/65937 | |
dc.description.abstract | New applications in recurrent neural networks are covered by this book, which will be required reading in the field. Methodological tools covered include ranking indices for fuzzy numbers, a neuro-fuzzy digital filter and mapping graphs of parallel programmes. The scope of the techniques profiled in real-world applications is evident from chapters on the recognition of severe weather patterns, adult and foetal ECGs in healthcare and the prediction of temperature time-series signals. Additional topics in this vein are the application of AI techniques to electromagnetic interference problems, bioprocess identification and I-term control and the use of BRNN-SVM to improve protein-domain prediction accuracy. Recurrent neural networks can also be used in virtual reality and nonlinear dynamical systems, as shown by two chapters. | |
dc.language | English | |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence | en_US |
dc.subject.other | Neural networks & fuzzy systems | |
dc.title | Recurrent Neural Networks and Soft Computing | |
dc.type | book | |
oapen.identifier.doi | 10.5772/2296 | |
oapen.relation.isPublishedBy | 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 | |
oapen.relation.isbn | 9789535104094 | |
oapen.relation.isbn | 9789535156208 | |
oapen.imprint | IntechOpen | |
oapen.pages | 304 |
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