An Improved Optimization Model to Predict the MOR of Glulam Prepared by UF-Oxidized Starch Adhesive: A Hybrid Artificial Neural Network-Modified Genetic Algorithm Optimization Approach

An Improved Optimization Model to Predict the MOR of Glulam Prepared by UF-Oxidized Starch Adhesive: A Hybrid Artificial Neural Network-Modified Genetic Algorithm Optimization Approach

The purpose of the present article is to study the bending strength of glulam prepared by plane tree (Platanus Orientalis-L) wood layers adhered by UF resin with different formaldehyde to urea molar ratios containing the modified starch adhesive with different NaOCl concentrations. Artificial neural...

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Bibliographic Details
Main Authors: Morteza Nazerian, Jalal Karimi, Hossin Jalali Torshizi, Antonios N. Papadopoulos, Sepideh Hamedi, Elham Vatankhah
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Materials
Subjects:
glulam
UF-modified starch adhesive
ANN
genetic algorithm
optimization
Online Access:https://www.mdpi.com/1996-1944/15/24/9074

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https://www.mdpi.com/1996-1944/15/24/9074

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