Optimal artificial neural network for data driven methane steam reforming model using bfgs quasi-newton

Methane steam reforming (MSR) is a commonly utilized method of hydrogen synthesis, contributing significantly to the global supply. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton method is an iterative technique for solving nonlinear optimization problems. This work investigates the use of...

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Bibliographic Details

Main Author:	Muhammad Hazman Kamil, Munauwir
Format:	Undergraduates Project Papers
Language:	en
Published:	2024
Subjects:	TA Engineering (General). Civil engineering (General) TP Chemical technology
Online Access:	https://umpir.ump.edu.my/id/eprint/47256/1/Optimal%20artificial%20neural%20network%20for%20data%20driven%20methane%20steam%20reforming%20model%20using%20bfgs%20quasi-newton.pdf https://umpir.ump.edu.my/id/eprint/47256/
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