Hevea Brasiliensis Oil Epoxidation: Hybrid Genetic Algorithm-Neural Fuzzy- Box-Behnken (Ga-Anfis-Bb) Modelling With Sensitivity And Uncertainty Analyses
ABSTRACT
Convectional
algorithms such as least-square and gradient descent for Adaptive Neuro-Fuzzy
Inference System (ANFIS) prediction of engineering process system is deficient
by local optimum trapping problem. Therefore, this study is aimed at developing
novel hybrid Genetic Algorithm (GA)-ANFIS- Box- Behken (BB) model for Hevea
Brasiliensis Seed Oil Epoxidation (HBSOE) prediction. Computer
codes for traditional ANFIS and hybrid GA-ANFIS modelling were written in
Matlab 2015 environment. Whereas BB numerical optimization technique of
Response Surface Methodology (RSM) of design expert V10 software was used to
select optimum GA-ANFIS tuning parameters (Population Size (PS), Crossover
Percentage (COP) and (MR): Mutation Rate). Sensitivity and uncertainty analyses
on GA-ANFIS-BB model output (MSE) were investigated using Monte Carlo
simulation in Crystal Ball software. ANFIS optimum result with gbell membership
function gave R2 (0.69651), MSE (0.0825). Optimum GA-ANFIS-BB parameters
(PS =90, COP=0.162, and MR=0.305) gave minimised MSE = 0.0085 and R2
= 0.998. The results showed that GA-ANFIS-BB predictability degree is higher
than ANFIS; thus, GA-ANFIS-BB predicted HBSOE satisfactorily. Mean Monte Carlo base case simulation gave
65.09% certainty of the MSE. Sensitivity analysis shows that COP and MR have 51.7.6%
and 26.6% negative percentage contribution on MSE respectively; while PS shows
a positive 21.7% contribution. Thus, GA-ANFIS-BB model in this study can be
used as a precursor and predictive tool for HBSOE fuzzy-based controller system
design
0.0
KENECHI, K (2022). Hevea Brasiliensis Oil Epoxidation: Hybrid Genetic Algorithm-Neural Fuzzy- Box-Behnken (Ga-Anfis-Bb) Modelling With Sensitivity And Uncertainty Analyses. Repository.mouau.edu.ng: Retrieved Dec 22, 2024, from https://repository.mouau.edu.ng/work/view/hevea-brasiliensis-oil-epoxidation-hybrid-genetic-algorithm-neural-fuzzy-box-behnken-ga-anfis-bb-modelling-with-sensitivity-and-uncertainty-analyses-7-2
KENECHI, KENECHI. "Hevea Brasiliensis Oil Epoxidation: Hybrid Genetic Algorithm-Neural Fuzzy- Box-Behnken (Ga-Anfis-Bb) Modelling With Sensitivity And Uncertainty Analyses" Repository.mouau.edu.ng. Repository.mouau.edu.ng, 27 Oct. 2022, https://repository.mouau.edu.ng/work/view/hevea-brasiliensis-oil-epoxidation-hybrid-genetic-algorithm-neural-fuzzy-box-behnken-ga-anfis-bb-modelling-with-sensitivity-and-uncertainty-analyses-7-2. Accessed 22 Dec. 2024.
KENECHI, KENECHI. "Hevea Brasiliensis Oil Epoxidation: Hybrid Genetic Algorithm-Neural Fuzzy- Box-Behnken (Ga-Anfis-Bb) Modelling With Sensitivity And Uncertainty Analyses". Repository.mouau.edu.ng, Repository.mouau.edu.ng, 27 Oct. 2022. Web. 22 Dec. 2024. < https://repository.mouau.edu.ng/work/view/hevea-brasiliensis-oil-epoxidation-hybrid-genetic-algorithm-neural-fuzzy-box-behnken-ga-anfis-bb-modelling-with-sensitivity-and-uncertainty-analyses-7-2 >.
KENECHI, KENECHI. "Hevea Brasiliensis Oil Epoxidation: Hybrid Genetic Algorithm-Neural Fuzzy- Box-Behnken (Ga-Anfis-Bb) Modelling With Sensitivity And Uncertainty Analyses" Repository.mouau.edu.ng (2022). Accessed 22 Dec. 2024. https://repository.mouau.edu.ng/work/view/hevea-brasiliensis-oil-epoxidation-hybrid-genetic-algorithm-neural-fuzzy-box-behnken-ga-anfis-bb-modelling-with-sensitivity-and-uncertainty-analyses-7-2