Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply

Mohd Amri Md Yunus; Mahdi Faramarzi; Sallehuddin Ibrahim; Wahid Ali Hamood Altowayti; Goh Pei San; Subhas Chandra Mukhopadhyay

doi:10.1109/ASCC.2015.7244593

Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply

Mohd Amri Md Yunus, Mahdi Faramarzi, Sallehuddin Ibrahim, Wahid Ali Hamood Altowayti, Goh Pei San, Subhas Chandra Mukhopadhyay

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

3 Citations (Scopus)

Abstract

This paper presents the comparisons between two models to classify nitrate and phosphate contamination in water supply based on artificial intelligence with multiple inputs parameters. The planar electromagnetic sensor array has been subjected to different water samples contaminated by nitrate and phosphate where output signals have been extracted. In the first method, the signals from the planar electromagnetic sensor array were derived to decompose by Wavelet Transform (WT). The energy and mean features of decomposed signals were extracted and used as inputs for an Artificial Neural Network (ANN) multilayer perceptron (MLP) and Radial Basis Function (RBF) neural networks models. The analysis models were targeted to classify the amount of nitrate and phosphate contamination in water supply. The result shows that the planar electromagnetic sensor array with the assistance of the MLP neural network method is the best alternative as compared to RBF neural network method.

Original language	English
Title of host publication	Emerging Control Techniques for a Sustainable World
Subtitle of host publication	2015 10th Asian Control Conference (ASCC 2015)
Place of Publication	Picataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781479978625
ISBN (Print)	9781479978632
DOIs	https://doi.org/10.1109/ASCC.2015.7244593
Publication status	Published - 8 Sep 2015
Externally published	Yes
Event	10th Asian Control Conference, ASCC 2015 - Kota Kinabalu, Malaysia Duration: 31 May 2015 → 3 Jun 2015

Other

Other	10th Asian Control Conference, ASCC 2015
Country/Territory	Malaysia
City	Kota Kinabalu
Period	31/05/15 → 3/06/15

Keywords

planar electromagnetic sensor array
artificial neural network
multi layer perceptron
radial basis function
feature extraction
nitrate and phosphate estimation

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10.1109/ASCC.2015.7244593

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Yunus, M. A. M., Faramarzi, M., Ibrahim, S., Altowayti, W. A. H., San, G. P., & Mukhopadhyay, S. C. (2015). Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. In Emerging Control Techniques for a Sustainable World: 2015 10th Asian Control Conference (ASCC 2015) (pp. 1-6). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ASCC.2015.7244593

Yunus, Mohd Amri Md ; Faramarzi, Mahdi ; Ibrahim, Sallehuddin ; Altowayti, Wahid Ali Hamood ; San, Goh Pei ; Mukhopadhyay, Subhas Chandra. / Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. Emerging Control Techniques for a Sustainable World: 2015 10th Asian Control Conference (ASCC 2015). Picataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2015. pp. 1-6

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title = "Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply",

abstract = "This paper presents the comparisons between two models to classify nitrate and phosphate contamination in water supply based on artificial intelligence with multiple inputs parameters. The planar electromagnetic sensor array has been subjected to different water samples contaminated by nitrate and phosphate where output signals have been extracted. In the first method, the signals from the planar electromagnetic sensor array were derived to decompose by Wavelet Transform (WT). The energy and mean features of decomposed signals were extracted and used as inputs for an Artificial Neural Network (ANN) multilayer perceptron (MLP) and Radial Basis Function (RBF) neural networks models. The analysis models were targeted to classify the amount of nitrate and phosphate contamination in water supply. The result shows that the planar electromagnetic sensor array with the assistance of the MLP neural network method is the best alternative as compared to RBF neural network method.",

keywords = "planar electromagnetic sensor array, artificial neural network, multi layer perceptron, radial basis function, feature extraction, nitrate and phosphate estimation",

author = "Yunus, {Mohd Amri Md} and Mahdi Faramarzi and Sallehuddin Ibrahim and Altowayti, {Wahid Ali Hamood} and San, {Goh Pei} and Mukhopadhyay, {Subhas Chandra}",

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Yunus, MAM, Faramarzi, M, Ibrahim, S, Altowayti, WAH, San, GP & Mukhopadhyay, SC 2015, Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. in Emerging Control Techniques for a Sustainable World: 2015 10th Asian Control Conference (ASCC 2015). Institute of Electrical and Electronics Engineers (IEEE), Picataway, NJ, pp. 1-6, 10th Asian Control Conference, ASCC 2015, Kota Kinabalu, Malaysia, 31/05/15. https://doi.org/10.1109/ASCC.2015.7244593

Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. / Yunus, Mohd Amri Md; Faramarzi, Mahdi; Ibrahim, Sallehuddin; Altowayti, Wahid Ali Hamood; San, Goh Pei; Mukhopadhyay, Subhas Chandra.

Emerging Control Techniques for a Sustainable World: 2015 10th Asian Control Conference (ASCC 2015). Picataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Yunus, Mohd Amri Md

AU - Faramarzi, Mahdi

AU - Ibrahim, Sallehuddin

AU - Altowayti, Wahid Ali Hamood

AU - San, Goh Pei

AU - Mukhopadhyay, Subhas Chandra

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N2 - This paper presents the comparisons between two models to classify nitrate and phosphate contamination in water supply based on artificial intelligence with multiple inputs parameters. The planar electromagnetic sensor array has been subjected to different water samples contaminated by nitrate and phosphate where output signals have been extracted. In the first method, the signals from the planar electromagnetic sensor array were derived to decompose by Wavelet Transform (WT). The energy and mean features of decomposed signals were extracted and used as inputs for an Artificial Neural Network (ANN) multilayer perceptron (MLP) and Radial Basis Function (RBF) neural networks models. The analysis models were targeted to classify the amount of nitrate and phosphate contamination in water supply. The result shows that the planar electromagnetic sensor array with the assistance of the MLP neural network method is the best alternative as compared to RBF neural network method.

AB - This paper presents the comparisons between two models to classify nitrate and phosphate contamination in water supply based on artificial intelligence with multiple inputs parameters. The planar electromagnetic sensor array has been subjected to different water samples contaminated by nitrate and phosphate where output signals have been extracted. In the first method, the signals from the planar electromagnetic sensor array were derived to decompose by Wavelet Transform (WT). The energy and mean features of decomposed signals were extracted and used as inputs for an Artificial Neural Network (ANN) multilayer perceptron (MLP) and Radial Basis Function (RBF) neural networks models. The analysis models were targeted to classify the amount of nitrate and phosphate contamination in water supply. The result shows that the planar electromagnetic sensor array with the assistance of the MLP neural network method is the best alternative as compared to RBF neural network method.

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Yunus MAM, Faramarzi M, Ibrahim S, Altowayti WAH, San GP, Mukhopadhyay SC. Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. In Emerging Control Techniques for a Sustainable World: 2015 10th Asian Control Conference (ASCC 2015). Picataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 1-6 https://doi.org/10.1109/ASCC.2015.7244593

Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply

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