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Titlebook: New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy L; Jonathan Amezcua,Patricia Melin,Osca

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發(fā)表于 2025-3-21 17:54:06 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy L
編輯Jonathan Amezcua,Patricia Melin,Oscar Castillo
視頻videohttp://file.papertrans.cn/665/664920/664920.mp4
概述Develops a new model for data classification.Presents a data classification model that is based on the competitive Neural Network Learning Vector Quantization (LVQ) and type-2 fuzzy logic
叢書(shū)名稱SpringerBriefs in Applied Sciences and Technology
圖書(shū)封面Titlebook: New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy L; Jonathan Amezcua,Patricia Melin,Osca
描述.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 ofsoil. Both datasets show interesting features that makes them interesting for testing new classification methods...?.
出版日期Book 2018
關(guān)鍵詞Computational Intelligence; Modular Neural Networks; LVQ; Type-2 Fuzzy Logic; Learning Vector Quantizati
版次1
doihttps://doi.org/10.1007/978-3-319-73773-7
isbn_softcover978-3-319-73772-0
isbn_ebook978-3-319-73773-7Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s) 2018
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:27:27 | 只看該作者
板凳
發(fā)表于 2025-3-22 00:36:57 | 只看該作者
Jonathan Amezcua,Patricia Melin,Oscar Castilloebensdauer nach einer Krebsoperation, nicht nur für die gesamte Erhebung, sondern auch für Teilgesamtheiten oder Schichten betrachten, die durch Kategorien anderer Merkmale oder Einflu?faktoren wie Baualterskategorien, m?nnliche bzw. weibliche W?hler, Behandlungsgruppen bestimmt sind. Durch den Verg
地板
發(fā)表于 2025-3-22 08:01:40 | 只看該作者
5#
發(fā)表于 2025-3-22 11:03:45 | 只看該作者
Book 2018 arrhythmias, and a satellite images segments dataset used for classifying six different types ofsoil. Both datasets show interesting features that makes them interesting for testing new classification methods...?.
6#
發(fā)表于 2025-3-22 16:36:44 | 只看該作者
2191-530X signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types ofsoil. Both datasets show interesting features that makes them interesting for testing new classification methods...?.978-3-319-73772-0978-3-319-73773-7Series ISSN 2191-530X Series E-ISSN 2191-5318
7#
發(fā)表于 2025-3-22 18:15:38 | 只看該作者
SpringerBriefs in Applied Sciences and Technologyhttp://image.papertrans.cn/n/image/664920.jpg
8#
發(fā)表于 2025-3-22 22:42:22 | 只看該作者
https://doi.org/10.1007/978-3-319-73773-7Computational Intelligence; Modular Neural Networks; LVQ; Type-2 Fuzzy Logic; Learning Vector Quantizati
9#
發(fā)表于 2025-3-23 02:22:03 | 只看該作者
Simulation Results,s was considered for training the models, and the 30% was used for testing. The testing sets were chosen randomly from the whole dataset, this means, the testing sets were always composed by different vectors for testing the models.
10#
發(fā)表于 2025-3-23 06:38:26 | 只看該作者
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