id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fis-5061	Kulkarni, Paresh; Chinchanikar, Satish	Modeling turning performance of Inconel 718 with hybrid nanofluid under MQL using ANN and ANFIS	2024	20	.pdf	application/pdf	10668	667	51	10 No of fuzzy rules 27 Weight of rules 1 No of nodes 78 No of linear parameters 27 No of non-linear parameters 27 No of training data pairs 15 Table 4: ANFIS model parameters. ANN parameter Characteristics Type of network Feed-forward backpropagation Type of training function TRAINLM Type of learning function LEARNGDM Performance function MSE (Mean Squared Error) Number of hidden layer(s) 1 Number of neurons on hidden layer 10 Number of epochs (max) 1000 Learning rate 0.001 Rate of train data (random) 70% Rate of test data (random) 30% Learning algorithm Levenberg-Marquardt backpropagation technique Transfer function Tansig (tangent sigmoid) Table 3: ANN model parameters and system configuration in the construction and analysis.	cache/fis-5061.pdf	txt/fis-5061.txt