Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network (ANN)
Salmonellosis is one of the most common seasonal zoonosis. As from the definition, zoonosis refers to the transmission of infectious diseases from animal to human. This paper presents the prediction of Salmonellosis incidence using Artificial Neural Network (ANN) on the basis of monthly data. A ser...
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my.utp.eprints.36392017-01-19T08:24:27Z Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network (ANN) Permanasari, Adhistya Erna Awang Rambli, Dayang Rohaya Dominic P, Dhanapal Durai QA75 Electronic computers. Computer science QL Zoology QA76 Computer software Salmonellosis is one of the most common seasonal zoonosis. As from the definition, zoonosis refers to the transmission of infectious diseases from animal to human. This paper presents the prediction of Salmonellosis incidence using Artificial Neural Network (ANN) on the basis of monthly data. A series of Salmonellosis incidence in US from 1993 to 2006,published by Centers for Disease Control and Prevention (CDC), was collected for technical analysis. Multi Layer Perceptron (MLP) has been chosen for the ANN design. The model consists of three layers: input layer, hidden layer, and output layer. Number of nodes in hidden layer was varied in order to find the most accurate forecasting result. The comparisons of models were justified by using Mean Absolute Percentage Error (MAPE). Furthermore, MAPE and Theil’s U were used to measure the result accuracy. The least MAPE derived from the best model was 10.761 and Theil’s U value was 0.209. It implied that the model was highly accurate and a close fit. It was also indicated the capability of final model to closely represent and made prediction based on the tuberculosis historical dataset. 2010-02 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/3639/1/stamp.jsp%3Farnumber%3D05451981%26tag%3D1 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05451981 Permanasari, Adhistya Erna and Awang Rambli, Dayang Rohaya and Dominic P, Dhanapal Durai (2010) Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network (ANN). In: 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010, 26-28 February 2010, Singapore. http://eprints.utp.edu.my/3639/ |
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QA75 Electronic computers. Computer science QL Zoology QA76 Computer software Permanasari, Adhistya Erna Awang Rambli, Dayang Rohaya Dominic P, Dhanapal Durai Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network (ANN) |
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Salmonellosis is one of the most common seasonal
zoonosis. As from the definition, zoonosis refers to the transmission of infectious diseases from animal to human. This paper presents the prediction of Salmonellosis incidence using Artificial Neural Network (ANN) on the basis of monthly data. A series of Salmonellosis incidence in US from 1993 to 2006,published by Centers for Disease Control and Prevention (CDC), was collected for technical analysis. Multi Layer Perceptron (MLP) has been chosen for the ANN design. The model consists of three layers: input layer, hidden layer, and output layer. Number of nodes in hidden layer was varied in order to find the most accurate forecasting result. The comparisons of models were justified by using Mean Absolute Percentage Error (MAPE). Furthermore, MAPE and Theil’s U were used to measure the result accuracy. The least MAPE derived from the best model was 10.761 and Theil’s U value was 0.209. It implied that the model was highly accurate and a close fit. It was also indicated the capability of final model to closely represent and made prediction based on the tuberculosis historical dataset. |
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Conference or Workshop Item |
author |
Permanasari, Adhistya Erna Awang Rambli, Dayang Rohaya Dominic P, Dhanapal Durai |
author_facet |
Permanasari, Adhistya Erna Awang Rambli, Dayang Rohaya Dominic P, Dhanapal Durai |
author_sort |
Permanasari, Adhistya Erna |
title |
Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network
(ANN) |
title_short |
Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network
(ANN) |
title_full |
Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network
(ANN) |
title_fullStr |
Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network
(ANN) |
title_full_unstemmed |
Forecasting of Salmonellosis Incidence in Human using Artificial Neural Network
(ANN) |
title_sort |
forecasting of salmonellosis incidence in human using artificial neural network
(ann) |
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2010 |
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http://eprints.utp.edu.my/3639/1/stamp.jsp%3Farnumber%3D05451981%26tag%3D1 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05451981 http://eprints.utp.edu.my/3639/ |
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13.160551 |