IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 9, No 2: June 2020

Evaluation of particle swarm optimization for strength determination of tropical wood polymer composite

Marina Yusoff (Universiti Teknologi MARA)
Alya Nurizzati Mohd Basir (Universiti Teknologi MARA)
Norhidayah A Kadir (Universiti Teknologi MARA)
Shahril Anuar Bahari (Universiti Teknologi MARA)



Article Info

Publish Date
01 Jun 2020

Abstract

A wood-polymer composite (WPCs) refers to wood-based components that are coupled with polymers to produce a composite material. Obtaining the best strength for the tropical WPCs is still a lack of research mainly for the tropical timber species and require a large consumption of time and cost. This paper highlighted the evaluation of particle swarm optimization (PSO) to assist in finding the optimal value of the composition of tropical WPCs to obtain the best strength that would offer a betterment in a quality product of WPCs. The findings demonstrate that PSO has been shown as a viable and efficient method for WPCs strength. The composition of Sentang, wood sawdust of 50%, HDPE of 49% and 1% coupling agent is demonstrated the best strength for the WPC. The employment of PSO as an assisted tool would give significant benefit to the manufacturer and researcher to determine the composition of material with less cost and time.

Copyrights © 2020






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...