Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network methods in herbal medicine related to oral health knowledge and practice
Herbal extracts have been utilized in oral health to treat various ailments, including inflammation, as antimicrobial plaque agents, antiseptics, antioxidants, histamine release prevention, and as antibacterial, antifungal, antiviral, and antimicrobial analgesics. Herbal medication also functions...
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| Format: | Thesis |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | http://eprints.usm.my/59768/ http://eprints.usm.my/59768/1/ABEDELMALEK%20KALEFH%20SLEEMAN%20TABNJH-FINAL%20THESIS%20P-SGD000121%28R%29%20-E.pdf |
| _version_ | 1848884259100557312 |
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| author | Tabnjh, Abedelmlek Kalefh Sleeman |
| author_facet | Tabnjh, Abedelmlek Kalefh Sleeman |
| author_sort | Tabnjh, Abedelmlek Kalefh Sleeman |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Herbal extracts have been utilized in oral health to treat various ailments,
including inflammation, as antimicrobial plaque agents, antiseptics, antioxidants,
histamine release prevention, and as antibacterial, antifungal, antiviral, and
antimicrobial analgesics. Herbal medication also functions in healing, plaque
reduction in the oral cavity, and immune enhancement. There is minimal research that
has used regression to link knowledge with practice and other sociodemographic
variables in HMOH. To develop a hybrid model by considering bootstrap, neural
network, and fuzzy regression for HMOH KP, to measure the efficacy and efficiency
of the developed hybrid model for HMOH KP, and to validate the newly developed
hybrid model. This study aims to develop the best strategy for handling data analysis,
especially in HMOH KP, which combines fuzzy regression and Multi-layer
Feedforward Neural Network (MLFFNN). R-programming software is used to write
the developed syntax. All the essential steps are summarized in the R syntax. The new
hybrid regression model incorporating bootstrapping, MLFFNN, and fuzzy regression
increases the precision of the estimated parameters and compensates for the ambiguous
relationship between the dependent and independent variables. The MLFFNN method
has successfully measured the effectiveness, efficiency, and accuracy of the new
hybrid model. The R2 value and the predicted value obtained are used to validate the derived model. Conclusion: This thesis presents a new methodology for creating
precise and validated regression models through the utilization of the HMOH KP
dataset. Moreover, this approach can be extended to any other dataset that aligns with
the provided assumptions. |
| first_indexed | 2025-11-15T19:03:51Z |
| format | Thesis |
| id | usm-59768 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:03:51Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-597682024-02-13T07:58:42Z http://eprints.usm.my/59768/ Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network methods in herbal medicine related to oral health knowledge and practice Tabnjh, Abedelmlek Kalefh Sleeman R Medicine RX Homeopathy Herbal extracts have been utilized in oral health to treat various ailments, including inflammation, as antimicrobial plaque agents, antiseptics, antioxidants, histamine release prevention, and as antibacterial, antifungal, antiviral, and antimicrobial analgesics. Herbal medication also functions in healing, plaque reduction in the oral cavity, and immune enhancement. There is minimal research that has used regression to link knowledge with practice and other sociodemographic variables in HMOH. To develop a hybrid model by considering bootstrap, neural network, and fuzzy regression for HMOH KP, to measure the efficacy and efficiency of the developed hybrid model for HMOH KP, and to validate the newly developed hybrid model. This study aims to develop the best strategy for handling data analysis, especially in HMOH KP, which combines fuzzy regression and Multi-layer Feedforward Neural Network (MLFFNN). R-programming software is used to write the developed syntax. All the essential steps are summarized in the R syntax. The new hybrid regression model incorporating bootstrapping, MLFFNN, and fuzzy regression increases the precision of the estimated parameters and compensates for the ambiguous relationship between the dependent and independent variables. The MLFFNN method has successfully measured the effectiveness, efficiency, and accuracy of the new hybrid model. The R2 value and the predicted value obtained are used to validate the derived model. Conclusion: This thesis presents a new methodology for creating precise and validated regression models through the utilization of the HMOH KP dataset. Moreover, this approach can be extended to any other dataset that aligns with the provided assumptions. 2023-08 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/59768/1/ABEDELMALEK%20KALEFH%20SLEEMAN%20TABNJH-FINAL%20THESIS%20P-SGD000121%28R%29%20-E.pdf Tabnjh, Abedelmlek Kalefh Sleeman (2023) Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network methods in herbal medicine related to oral health knowledge and practice. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | R Medicine RX Homeopathy Tabnjh, Abedelmlek Kalefh Sleeman Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network methods in herbal medicine related to oral health knowledge and practice |
| title | Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| title_full | Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| title_fullStr | Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| title_full_unstemmed | Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| title_short | Development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| title_sort | development of a new hybrid regression model: an application of fuzzy regression and multilayer feedforward neural network
methods in herbal medicine related
to oral health knowledge and
practice |
| topic | R Medicine RX Homeopathy |
| url | http://eprints.usm.my/59768/ http://eprints.usm.my/59768/1/ABEDELMALEK%20KALEFH%20SLEEMAN%20TABNJH-FINAL%20THESIS%20P-SGD000121%28R%29%20-E.pdf |