Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model

Table 7

Comparison of developed ANFIS and previous models found in the literature.

Model type	Input	Output	Validation (R^2 value)	Reference
ANFIS	Delivery speed, break draft, and distance between the back and middle rolls	Breaking strength	0.4800	Fallahpour and Moghassem [57]
Gene expression programming (GEP) models	Delivery speed, break draft, and distance between the back and middle rolls	Breaking strength	0.8700	Fallahpour and Moghassem [57]
Multilayered feed-forward neural network	Mass amount of pineapple peel, pH of the inlet, COD of the inlet, volatile fatty acids (VFA) of the inlet, and volatile solids (VS) of the inlet	VS of the outlet, the volume of biogas, and the methane fraction of biogas	0.9942	Jaroenpoj et al. [58]
ANFIS	pH, temperature, time, yeast extraction concentration, and K2HPO4	Polygalacturonase activity	0.9780	Uzuner and Cekmecelioglu [59]
ANN	pH, temperature, time, yeast extraction concentration, and K2HPO4	Polygalacturonase activity	1.0000	Uzuner and Cekmecelioglu [59]
ANFIS	Cherry tomatoes, storage temperature, and storage time	Physicochemical and microbiological parameters	>0.86	Tao et al. [60]
ANFIS	Solar radiation, relative humidity, total dissolved solids of the feed, total dissolved solids of the brine, and feed flow rate	Solar still productivity	0.9900	Mashaly and Alazba [61]
ANFIS	Velocity distribution and CFD iteration time	Temperature	0.9990	Babanezhad et al. [62]
ANN	Cutting speed, feed rate, and depth of cut	Metal removal rate and tool wear	0.9210	Sada and Ikpeseni [63]
ANFIS	Cutting speed, feed rate, and depth of cut	Metal removal rate; tool wear	0.7300	Sada and Ikpeseni [63]
Bayesian-ANFIS	Class record and exam performance	Student performance	0.7990	Makolo and Olapojoye [64]
ANFIS	Temperature and pressure	Biogas yield	0.9978	Present study [38]