Using Non-supervised Artificial Neural Network for Determination of Anthropogenic Disturbance in a River System

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Nurul Ruhayu Mohd Rosli
Khairun Yahya


The study of river water quality plays an important role in assessing the pollution status and health of the water bodies. Human-induced activities such as domestic activities, aquaculture, agriculture and industries have detrimentally affected the river water quality. Pinang River is one of the important rivers in Balik Pulau District that supplies freshwater for human consumption. A total of 442 physical and chemical parameters data of the Pinang River, Balik Pulau catchment were analysed to determine the sources of pollutants entering the river. Non-supervised artificial neural network (ANN) was employed to classify and cluster the river into upstream, middle-stream and downstream zones. The monitored data and nonsupervised ANN analysis demonstrated that the source of nitrate was derived from the upper part of the Pinang River, Balik Pulau while the sources of nitrite, ammonia and ortho-phosphate are predominant at the middle-stream of the river system. Meanwhile, the sources of high total suspended solid and biological oxygen demand were concentrated at the downstream of the river.


Kajian kualiti air sungai memainkan peranan yang penting dalam menilai status pencemaran dan kesihatan air. Aktiviti manusia seperti domestik, akuakultur, pertanian dan industri telah menjejaskan kualiti air sungai. Sungai Pinang adalah salah satu sungai penting di daerah Balik Pulau, yang membekalkan air tawar untuk kegunaan manusia. Parameter fizikal dan kimia di kawasan tadahan Sungai Pinang, Balik Pulau dianalisis untuk menentukan sumber bahan pencemaran yang memasuki sungai. ?Non-supervised artificial neural network? (ANN) telah digunakan untuk mengkelas dan mengkluster sungai kepada bahagian hulu, tengah dan hilir. Data yang dipantau dan analisis nonsupervised ANN menunjukkan bahawa sumber nitrat berasal dari bahagian hulu Sungai Pinang, Balik Pulau, manakala sumber nitrit, ammonia dan orto-fosfat mempunyai pengaruh besar di bahagian tengah sistem sungai. Sementara itu, jumlah tinggi pepejal terampai dan keperluan oksigen biologi tertumpu di hilir sungai.

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Nurul Ruhayu Mohd Rosli, & Khairun Yahya. (2017). Using Non-supervised Artificial Neural Network for Determination of Anthropogenic Disturbance in a River System. Tropical Life Sciences Research, 28(2), 189–199.
Original Article


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