Modeling the Optical Properties of a Polyvinyl Alcohol-Based Composite Using a Particle Swarm Optimized Support Vector Regression Algorithm

We developed particle swarm optimization-based support vector regression (PSVR) and ordinary linear regression (OLR) models for estimating the refractive index (n) and energy gap (E) of a polyvinyl alcohol composite. The n-PSVR model, which can estimate the refractive index of a polyvinyl alcohol co...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Polymers Ročník 13; číslo 16; s. 2697
Hlavní autori: Owolabi, Taoreed O., Abd Rahman, Mohd Amiruddin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 12.08.2021
MDPI
Predmet:
Algorithms
Carbon
Dysprosium
Energy
Energy gap
Incorporation
Mechanical properties
Optical properties
Optimization
Particle swarm optimization
Polymer matrix composites
Polymers
Polyvinyl alcohol
Prediction models
Refractivity
Regression
Regression analysis
Root-mean-square errors
Support vector machines
ISSN:2073-4360, 2073-4360
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:We developed particle swarm optimization-based support vector regression (PSVR) and ordinary linear regression (OLR) models for estimating the refractive index (n) and energy gap (E) of a polyvinyl alcohol composite. The n-PSVR model, which can estimate the refractive index of a polyvinyl alcohol composite using the energy gap as a descriptor, performed better than the n-OLR model in terms of root mean square error (RMSE) and mean absolute error (MAE) metrics. The E-PSVR model, which can predict the energy gap of a polyvinyl alcohol composite using its refractive index descriptor, outperformed the E-OLR model, which uses similar descriptor based on several performance measuring metrics. The n-PSVR and E-PSVR models were used to investigate the influences of sodium-based dysprosium oxide and benzoxazinone derivatives on the energy gaps of a polyvinyl alcohol polymer composite. The results agreed well with the measured values. The models had low mean absolute percentage errors after validation with external data. The precision demonstrated by these predictive models will enhance the tailoring of the optical properties of polyvinyl alcohol composites for the desired applications. Costs and experimental difficulties will be reduced.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2073-4360
2073-4360
DOI:10.3390/polym13162697