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Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm

This study shows a new method to estimate unsampled pH value by utilizing neighboring pH, which according to recent literature, has not been done yet. In investigating this method, three algorithms are used: Neural Network-Genetic Algorithm (MLNN-GA), MLNN with backpropagation (MLNN-BP), and averagi...

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Main Authors: Muhammad Aznil, Ab Aziz, Mohammad Fadhil, Abas, Muhamad Abdul Hasib, Ali, Norhafidzah, Mohd Saad, Mohd Hisyam, Ariff, Mohamad Khairul Anwar, Abu Bashrin
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/38779/1/Estimating%20the%20Un-sampled%20pH%20Value%20via%20neighbouring%20points.pdf
http://umpir.ump.edu.my/id/eprint/38779/2/Estimating%20the%20un-sampled%20ph%20value%20via%20neighbouring%20points%20using%20multi-layer%20neural%20network%20-%20genetic%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/38779/
https://doi.org/10.1109/CSPA57446.2023.10087388
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spelling my.ump.umpir.387792023-11-06T06:53:58Z http://umpir.ump.edu.my/id/eprint/38779/ Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm Muhammad Aznil, Ab Aziz Mohammad Fadhil, Abas Muhamad Abdul Hasib, Ali Norhafidzah, Mohd Saad Mohd Hisyam, Ariff Mohamad Khairul Anwar, Abu Bashrin T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This study shows a new method to estimate unsampled pH value by utilizing neighboring pH, which according to recent literature, has not been done yet. In investigating this method, three algorithms are used: Neural Network-Genetic Algorithm (MLNN-GA), MLNN with backpropagation (MLNN-BP), and averaging method. MLNNGA and MLNN-BP are inputted with four pH values from distant adjacent locations on a similar basin. MLNN-GA and MLNN-BP utilize GA and backpropagation respectively to update the weight. GA optimizer is used in MLNN-GA where the result of each learning weight will be the initial weight of the next learning process. All three methods are compared based on RMSE, MSE and MAPE. MLNN-GA yielded the lowest average RMSE =0.026265, average MSE =0.000886 and average MAPE =0.003985 compared to MLNN-BP (average RMSE =0.042644, average MSE =0.002648, average MAPE =0.006862) and averaging method (average RMSE =0.136629, average MSE = 0.026128, average MAPE =0.150400). Noticeably, estimating unsampled pH value utilizing neighboring pH by using MLNNGA shows a better performance than MLNN-BP and averaging method. Institute of Electrical and Electronics Engineers Inc. 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38779/1/Estimating%20the%20Un-sampled%20pH%20Value%20via%20neighbouring%20points.pdf pdf en http://umpir.ump.edu.my/id/eprint/38779/2/Estimating%20the%20un-sampled%20ph%20value%20via%20neighbouring%20points%20using%20multi-layer%20neural%20network%20-%20genetic%20algorithm_ABS.pdf Muhammad Aznil, Ab Aziz and Mohammad Fadhil, Abas and Muhamad Abdul Hasib, Ali and Norhafidzah, Mohd Saad and Mohd Hisyam, Ariff and Mohamad Khairul Anwar, Abu Bashrin (2023) Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm. In: 2023 19th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2023 - Conference Proceedings, 3-4 March 2023 , Kedah. pp. 207-212.. ISBN 978-166547692-8 https://doi.org/10.1109/CSPA57446.2023.10087388
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Muhammad Aznil, Ab Aziz
Mohammad Fadhil, Abas
Muhamad Abdul Hasib, Ali
Norhafidzah, Mohd Saad
Mohd Hisyam, Ariff
Mohamad Khairul Anwar, Abu Bashrin
Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
description This study shows a new method to estimate unsampled pH value by utilizing neighboring pH, which according to recent literature, has not been done yet. In investigating this method, three algorithms are used: Neural Network-Genetic Algorithm (MLNN-GA), MLNN with backpropagation (MLNN-BP), and averaging method. MLNNGA and MLNN-BP are inputted with four pH values from distant adjacent locations on a similar basin. MLNN-GA and MLNN-BP utilize GA and backpropagation respectively to update the weight. GA optimizer is used in MLNN-GA where the result of each learning weight will be the initial weight of the next learning process. All three methods are compared based on RMSE, MSE and MAPE. MLNN-GA yielded the lowest average RMSE =0.026265, average MSE =0.000886 and average MAPE =0.003985 compared to MLNN-BP (average RMSE =0.042644, average MSE =0.002648, average MAPE =0.006862) and averaging method (average RMSE =0.136629, average MSE = 0.026128, average MAPE =0.150400). Noticeably, estimating unsampled pH value utilizing neighboring pH by using MLNNGA shows a better performance than MLNN-BP and averaging method.
format Conference or Workshop Item
author Muhammad Aznil, Ab Aziz
Mohammad Fadhil, Abas
Muhamad Abdul Hasib, Ali
Norhafidzah, Mohd Saad
Mohd Hisyam, Ariff
Mohamad Khairul Anwar, Abu Bashrin
author_facet Muhammad Aznil, Ab Aziz
Mohammad Fadhil, Abas
Muhamad Abdul Hasib, Ali
Norhafidzah, Mohd Saad
Mohd Hisyam, Ariff
Mohamad Khairul Anwar, Abu Bashrin
author_sort Muhammad Aznil, Ab Aziz
title Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
title_short Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
title_full Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
title_fullStr Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
title_full_unstemmed Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
title_sort estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/38779/1/Estimating%20the%20Un-sampled%20pH%20Value%20via%20neighbouring%20points.pdf
http://umpir.ump.edu.my/id/eprint/38779/2/Estimating%20the%20un-sampled%20ph%20value%20via%20neighbouring%20points%20using%20multi-layer%20neural%20network%20-%20genetic%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/38779/
https://doi.org/10.1109/CSPA57446.2023.10087388
_version_ 1822923748707139584
score 13.232414

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