Three-Layer Weighted Fuzzy Support Vector Regressions for Emotional Intention Understanding

Luefeng Chen*, Min Wu, Witold Pedrycz, Kaoru Hirota

*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

1 引用 （Scopus）
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摘要

A three-layer weighted fuzzy support vector regression (TLWFSVR) model is proposed for understanding human intention, and it is based on the emotion-identification information in human-robot interaction. TLWFSVR model consists of three layers, including adjusted weighted kernel fuzzy c-means (AWKFCM) for data clustering, fuzzy support vector regressions (FSVR) for information understanding, and weighted fusion for intention understanding.

源语言英语
主期刊名Studies in Computational Intelligence
出版商Springer Science and Business Media Deutschland GmbH
页133-159
页数27
DOI
出版状态已出版 - 2021
已对外发布是

出版系列

姓名Studies in Computational Intelligence
卷926
ISSN（印刷版）1860-949X
ISSN（电子版）1860-9503

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引用此

Chen, L., Wu, M., Pedrycz, W., & Hirota, K. (2021). Three-Layer Weighted Fuzzy Support Vector Regressions for Emotional Intention Understanding. 在 Studies in Computational Intelligence (页码 133-159). (Studies in Computational Intelligence; 卷 926). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-61577-2_9