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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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | http://eprints.usm.my/59768/1/ABEDELMALEK%20KALEFH%20SLEEMAN%20TABNJH-FINAL%20THESIS%20P-SGD000121%28R%29%20-E.pdf |
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| Summary: | 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. |
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