Mean-variance model with fuzzy random data
This paper recommends discourse feeling acknowledgment from discourse signal dependent on highlights examination and PNN-classifier. The arrangement of acknowledgment incorporates discovery of discourse feelings, extraction and determination of highlights, lastly characterization. These highlights a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Innovare Academics Sciences PVT. LTD
2020
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6558/ http://eprints.uthm.edu.my/6558/1/AJ%202020%20%28355%29.pdf |
| _version_ | 1848888843977097216 |
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| author | Othman, Mohammad Haris Haikal Arbaiy, Nureize Che Lah, Muhammad Shukri Pei, Chun Lin |
| author_facet | Othman, Mohammad Haris Haikal Arbaiy, Nureize Che Lah, Muhammad Shukri Pei, Chun Lin |
| author_sort | Othman, Mohammad Haris Haikal |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | This paper recommends discourse feeling acknowledgment from discourse signal dependent on highlights examination and PNN-classifier. The arrangement of acknowledgment incorporates discovery of discourse feelings, extraction and determination of highlights, lastly characterization. These highlights are valued to segregate the greatest number of tests precisely and the PNN classifier dependent on discriminant investigation is utilized to characterize the six distinctive articulations. The reproduced outcomes will be indicated that the channel occupied component extortion with utilized distribution presents much better exactness with less algorithmic unpredictability than other discourse feeling articulation acknowledgment draws near. |
| first_indexed | 2025-11-15T20:16:44Z |
| format | Article |
| id | uthm-6558 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:16:44Z |
| publishDate | 2020 |
| publisher | Innovare Academics Sciences PVT. LTD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-65582022-03-01T03:58:12Z http://eprints.uthm.edu.my/6558/ Mean-variance model with fuzzy random data Othman, Mohammad Haris Haikal Arbaiy, Nureize Che Lah, Muhammad Shukri Pei, Chun Lin QA1-43 General This paper recommends discourse feeling acknowledgment from discourse signal dependent on highlights examination and PNN-classifier. The arrangement of acknowledgment incorporates discovery of discourse feelings, extraction and determination of highlights, lastly characterization. These highlights are valued to segregate the greatest number of tests precisely and the PNN classifier dependent on discriminant investigation is utilized to characterize the six distinctive articulations. The reproduced outcomes will be indicated that the channel occupied component extortion with utilized distribution presents much better exactness with less algorithmic unpredictability than other discourse feeling articulation acknowledgment draws near. Innovare Academics Sciences PVT. LTD 2020 Article PeerReviewed text en http://eprints.uthm.edu.my/6558/1/AJ%202020%20%28355%29.pdf Othman, Mohammad Haris Haikal and Arbaiy, Nureize and Che Lah, Muhammad Shukri and Pei, Chun Lin (2020) Mean-variance model with fuzzy random data. Journal of Critical Reviews, 7 (8). pp. 1347-1352. ISSN 2394-5125 http://dx.doi.org/10.31838/jcr.07.08.272 |
| spellingShingle | QA1-43 General Othman, Mohammad Haris Haikal Arbaiy, Nureize Che Lah, Muhammad Shukri Pei, Chun Lin Mean-variance model with fuzzy random data |
| title | Mean-variance model with fuzzy random data |
| title_full | Mean-variance model with fuzzy random data |
| title_fullStr | Mean-variance model with fuzzy random data |
| title_full_unstemmed | Mean-variance model with fuzzy random data |
| title_short | Mean-variance model with fuzzy random data |
| title_sort | mean-variance model with fuzzy random data |
| topic | QA1-43 General |
| url | http://eprints.uthm.edu.my/6558/ http://eprints.uthm.edu.my/6558/ http://eprints.uthm.edu.my/6558/1/AJ%202020%20%28355%29.pdf |