New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic (Record no. 79746)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03198nam a22005175i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-73773-7 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801221517.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 180207s2018 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319737737 |
| -- | 978-3-319-73773-7 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Amezcua, Jonathan. |
| 245 10 - TITLE STATEMENT | |
| Title | New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2018. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | VIII, 73 p. 22 illus., 12 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | SpringerBriefs in Computational Intelligence, |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector Quantization (LVQ) and type-2 fuzzy logic. This computational model consists of the hybridization of the aforementioned techniques, using a fuzzy logic system within the competitive layer of the LVQ network to determine the shortest distance between a centroid and an input vector. This new model is based on a modular LVQ architecture to further improve its performance on complex classification problems. It also implements a data-similarity process for preprocessing the datasets, in order to build dynamic architectures, having the classes with the highest degree of similarity in different modules. Some architectures were developed in order to work mainly with two datasets, an arrhythmia dataset (using ECG signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types of soil. Both datasets show interesting features that makes them interesting for testing new classification methods. . |
| 700 1# - AUTHOR 2 | |
| Author 2 | Melin, Patricia. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Castillo, Oscar. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-73773-7 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2018. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2625-3712 |
| 912 ## - | |
| -- | ZDB-2-ENG |
| 912 ## - | |
| -- | ZDB-2-SXE |
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