id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-3666	Rohit Khatri	Artificial Neural Network Approach to Multi-Response Prediction of Transesterification 	2025	8	.pdf	application/pdf	3169	147	48	No. 8s (2025) 235 https://internationalpubls.com Figure1 Regression curves for biodiesel yield Figure2 Regression curves for biodiesel Kinematic viscosity In training phase, high value of correlation coefficient (R) 0.99874 & 0.9976 and alignment of Regression line with data for yield and kinematic viscosity respectively, indicates model’s capability to establish relationship between predicted and actual values. [5] G. M. Lionus Leo, R. Jayabal, D. Srinivasan, M. Chrispin Das, M. Ganesh, and T. Gavaskar, “Predicting the performance and emissions of an HCCI-DI engine powered by waste cooking oil biodiesel with Al2O3 and FeCl3 nano additives and gasoline injection – A random forest machine learning approach,” Fuel, vol. 357, p. 129914, Feb. 2024, doi: 10.1016/j.fuel.2023.129914.	cache/cana-3666.pdf	txt/cana-3666.txt