Accurate modeling of biodiesel production from castor oil using ANFIS

Yue, Xiaoyun; Chen, Yehua; Chang, Guoyang

doi:10.1080/15567036.2017.1422058

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Prediction Efficiency Of Anfis Model For Oil Yield1

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Cited by 11 publications

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“…From a statistical performance point of view, the prediction of oil yield for huracrepitan seed is poor compared to the other existing investigation on ANFIS modelling. [20][21][22]…”

Section: Prediction Efficiency Of Anfis Model For Oil Yieldmentioning

confidence: 99%

Soft Computing Prediction of Oil Extraction from Huracrepitan Seeds

2020

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This study analyses the extraction process parameters of huracrepitan seed oil using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). The experiments were conducted at temperature (60–80 °C), time (4–6 h), and solute/solvent ratio (0.05–0.10) with output parameter as oil yield. Sensitivity analysis shows that temperature and time had the most significant effect on the oil yield. The oil yield estimation performance indicators are: ANN (R2 = 0.999, MSE = 5.63192E-13), ANFIS (R2 = 0.36927, MSE = 0.42331). The results show that ANN gave a better prediction than ANFIS.

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“…From a statistical performance point of view, the prediction of oil yield for huracrepitan seed is poor compared to the other existing investigation on ANFIS modelling. [20][21][22]…”

Section: Prediction Efficiency Of Anfis Model For Oil Yieldmentioning

confidence: 99%