Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm

Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm

In this paper, artificial neural network had been implemented to model the biodelignification process of oil palm trunk core using Pleurotus Ostreatus. The generated model was used as the fitness function for the genetic algorithm to obtain the optimise lignin left percentage. The 4-10-5-2-1 network...

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Main Authors: Abdul Sahli, Fakharudin, Norazwina, Zainol, Zulsyazwan, Ahmad Khushairi
Format: Conference or Workshop Item
Language:English
English
Published: Association for Computing Machinery (ACM) 2019
Subjects:
QA76 Computer software
TP Chemical technology
Online Access:http://umpir.ump.edu.my/id/eprint/24700/
http://umpir.ump.edu.my/id/eprint/24700/
http://umpir.ump.edu.my/id/eprint/24700/1/36.%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/24700/2/36.1%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf
id ump-24700
recordtype eprints
spelling ump-247002019-08-26T02:33:29Z http://umpir.ump.edu.my/id/eprint/24700/ Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm Abdul Sahli, Fakharudin Norazwina, Zainol Zulsyazwan, Ahmad Khushairi QA76 Computer software TP Chemical technology In this paper, artificial neural network had been implemented to model the biodelignification process of oil palm trunk core using Pleurotus Ostreatus. The generated model was used as the fitness function for the genetic algorithm to obtain the optimise lignin left percentage. The 4-10-5-2-1 network architecture had been used to model the process and 10 models were generated randomly. These models were used to find the optimised the network output using genetic algorithm search. The modelling results had improved the accuracy and error when using the artificial neural network modelling with training MSE of 0.0096 and testing MSE of 0.2108. The results also show an improved lignin left around 7.55% when the network output was optimised by the genetic algorithm. The application of neural network and genetic algorithm had improved the delignification process. Association for Computing Machinery (ACM) 2019-03 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24700/1/36.%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/24700/2/36.1%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf Abdul Sahli, Fakharudin and Norazwina, Zainol and Zulsyazwan, Ahmad Khushairi (2019) Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm. In: 8th International Conference on Informatics, Environment, Energy and Applications 2019, 16 - 19 March 2019 , Osaka, Japan. pp. 155-158.. ISBN 978-145036104-0 https://doi.org/10.1145/3323716.3323737
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic QA76 Computer software
TP Chemical technology
spellingShingle QA76 Computer software
TP Chemical technology
Abdul Sahli, Fakharudin
Norazwina, Zainol
Zulsyazwan, Ahmad Khushairi
Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
description In this paper, artificial neural network had been implemented to model the biodelignification process of oil palm trunk core using Pleurotus Ostreatus. The generated model was used as the fitness function for the genetic algorithm to obtain the optimise lignin left percentage. The 4-10-5-2-1 network architecture had been used to model the process and 10 models were generated randomly. These models were used to find the optimised the network output using genetic algorithm search. The modelling results had improved the accuracy and error when using the artificial neural network modelling with training MSE of 0.0096 and testing MSE of 0.2108. The results also show an improved lignin left around 7.55% when the network output was optimised by the genetic algorithm. The application of neural network and genetic algorithm had improved the delignification process.
format Conference or Workshop Item
author Abdul Sahli, Fakharudin
Norazwina, Zainol
Zulsyazwan, Ahmad Khushairi
author_facet Abdul Sahli, Fakharudin
Norazwina, Zainol
Zulsyazwan, Ahmad Khushairi
author_sort Abdul Sahli, Fakharudin
title Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
title_short Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
title_full Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
title_fullStr Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
title_full_unstemmed Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
title_sort modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm
publisher Association for Computing Machinery (ACM)
publishDate 2019
url http://umpir.ump.edu.my/id/eprint/24700/
http://umpir.ump.edu.my/id/eprint/24700/
http://umpir.ump.edu.my/id/eprint/24700/1/36.%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/24700/2/36.1%20Modelling%20and%20optimisation%20of%20oil%20palm%20trunk%20core%20biodelignification%20using%20neural%20network%20and%20genetic%20algorithm.pdf
first_indexed 2023-09-18T22:37:32Z
last_indexed 2023-09-18T22:37:32Z
_version_ 1777416696182603776

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