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...

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Main Authors: Othman, Mohammad Haris Haikal, Arbaiy, Nureize, Che Lah, Muhammad Shukri, Pei, Chun Lin
Format: Article
Language:English
Published: Innovare Academics Sciences PVT. LTD 2020
Subjects:
Online Access:http://eprints.uthm.edu.my/6558/
http://eprints.uthm.edu.my/6558/1/AJ%202020%20%28355%29.pdf
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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
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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