Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply
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 p...
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2015
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author | Md. Yunus, Mohd. Amri Faramarzi, Mahdi Ibrahim, Sallehuddin Altowayti, Wahid Ali Hamood Goh, Pei San Mukhopadhyay, Subhas Chandra |
author_facet | Md. Yunus, Mohd. Amri Faramarzi, Mahdi Ibrahim, Sallehuddin Altowayti, Wahid Ali Hamood Goh, Pei San Mukhopadhyay, Subhas Chandra |
author_sort | Md. Yunus, Mohd. Amri |
collection | ePrints |
description | 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. |
first_indexed | 2024-03-05T19:48:51Z |
format | Conference or Workshop Item |
id | utm.eprints-60620 |
institution | Universiti Teknologi Malaysia - ePrints |
last_indexed | 2024-03-05T19:48:51Z |
publishDate | 2015 |
record_format | dspace |
spelling | utm.eprints-606202017-08-06T06:44:01Z http://eprints.utm.my/60620/ Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply Md. Yunus, Mohd. Amri Faramarzi, Mahdi Ibrahim, Sallehuddin Altowayti, Wahid Ali Hamood Goh, Pei San Mukhopadhyay, Subhas Chandra QA Mathematics 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. 2015 Conference or Workshop Item PeerReviewed Md. Yunus, Mohd. Amri and Faramarzi, Mahdi and Ibrahim, Sallehuddin and Altowayti, Wahid Ali Hamood and Goh, Pei San and Mukhopadhyay, Subhas Chandra (2015) Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply. In: Proceeding of the 10th Asian Control Conference, 31 May - 3 Jun, 2015, Sabah, Malaysia. http://ieeexplore.ieee.org/document/7244593/ |
spellingShingle | QA Mathematics Md. Yunus, Mohd. Amri Faramarzi, Mahdi Ibrahim, Sallehuddin Altowayti, Wahid Ali Hamood Goh, Pei San Mukhopadhyay, Subhas Chandra Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title | Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title_full | Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title_fullStr | Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title_full_unstemmed | Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title_short | Comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
title_sort | comparisons between radial basis function and multilayer perceptron neural networks methods for nitrate and phosphate detections in water supply |
topic | QA Mathematics |
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