Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia

Five years of data from 2001 until 2006 of warm unstratified shallow, oligotrophic to mesothropic tropical Putrajaya Lake, Malaysia were used to study pattern discovery and forecasting of the diatom abundance using supervised and unsupervised artificial neural networks. Recurrent artificial neural n...

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Main Authors: Sorayya, M, Aishah,, Mohd. Sapiyan, B
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2012
Online Access:http://journalarticle.ukm.my/5414/1/01%2520M.sorayya.pdf
http://journalarticle.ukm.my/5414/
http://www.ukm.my/jsm
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spelling my-ukm.journal.54142016-12-14T06:38:23Z http://journalarticle.ukm.my/5414/ Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia Sorayya, M Aishah, Mohd. Sapiyan, B Five years of data from 2001 until 2006 of warm unstratified shallow, oligotrophic to mesothropic tropical Putrajaya Lake, Malaysia were used to study pattern discovery and forecasting of the diatom abundance using supervised and unsupervised artificial neural networks. Recurrent artificial neural network (RANN) was used for the supervised artificial neural network and Kohonen Self Organizing Feature Maps (SOM) was used for unsupervised artificial neural network. RANN was applied for forecasting of diatom abundance. The RANN performance was measured in terms of root mean square error (RMSE) and the value reported was 29.12 cell/mL. Classification and clustering by SOM and sensitivity analysis from the RANN were used to reveal the relationship among water temperature, pH, nitrate nitrogen (NO3-N) concentration, chemical oxygen demand (COD) concentration and diatom abundance. The results indicated that the combination of supervised and unsupervised artificial neural network is important not only for forecasting algae abundance but also in reasoning and understanding ecological relationships. This in return will assist in better management of lake water quality. Universiti Kebangsaan Malaysia 2012-08 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/5414/1/01%2520M.sorayya.pdf Sorayya, M and Aishah, and Mohd. Sapiyan, B (2012) Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia. Sains Malaysiana, 41 (8). pp. 939-947. ISSN 0126-6039 http://www.ukm.my/jsm
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Five years of data from 2001 until 2006 of warm unstratified shallow, oligotrophic to mesothropic tropical Putrajaya Lake, Malaysia were used to study pattern discovery and forecasting of the diatom abundance using supervised and unsupervised artificial neural networks. Recurrent artificial neural network (RANN) was used for the supervised artificial neural network and Kohonen Self Organizing Feature Maps (SOM) was used for unsupervised artificial neural network. RANN was applied for forecasting of diatom abundance. The RANN performance was measured in terms of root mean square error (RMSE) and the value reported was 29.12 cell/mL. Classification and clustering by SOM and sensitivity analysis from the RANN were used to reveal the relationship among water temperature, pH, nitrate nitrogen (NO3-N) concentration, chemical oxygen demand (COD) concentration and diatom abundance. The results indicated that the combination of supervised and unsupervised artificial neural network is important not only for forecasting algae abundance but also in reasoning and understanding ecological relationships. This in return will assist in better management of lake water quality.
format Article
author Sorayya, M
Aishah,
Mohd. Sapiyan, B
spellingShingle Sorayya, M
Aishah,
Mohd. Sapiyan, B
Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
author_facet Sorayya, M
Aishah,
Mohd. Sapiyan, B
author_sort Sorayya, M
title Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
title_short Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
title_full Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
title_fullStr Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
title_full_unstemmed Supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical Putrajaya Lake, Malaysia
title_sort supervised and unsupervised artificial neural networks for analysis of diatom abundance in tropical putrajaya lake, malaysia
publisher Universiti Kebangsaan Malaysia
publishDate 2012
url http://journalarticle.ukm.my/5414/1/01%2520M.sorayya.pdf
http://journalarticle.ukm.my/5414/
http://www.ukm.my/jsm
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score 13.211869