Citation
Kamarul Ismail, . and Ruslan Rainis, . (2004) Modeling river water quality index using artificial neural networks and geographical information system. [Proceedings Paper]
Abstract
This paper reports our initial attempt to use Artificial Neural Network ANN to model river water quality index WQI based on land use data. Geographical Information System GIS was used to assist in generating the necessary spatial data especially land use data. The ANN model was trained using SFAM Simplified Fuzzy Adaptive Resonance Theory Map. The accuracy of the model is quite acceptable where the accuracy during the model development and validation were 97 and 86 respectively.
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Abstract
This paper reports our initial attempt to use Artificial Neural Network ANN to model river water quality index WQI based on land use data. Geographical Information System GIS was used to assist in generating the necessary spatial data especially land use data. The ANN model was trained using SFAM Simplified Fuzzy Adaptive Resonance Theory Map. The accuracy of the model is quite acceptable where the accuracy during the model development and validation were 97 and 86 respectively.
Additional Metadata
| Item Type: | Proceedings Paper |
|---|---|
| Additional Information: | Summary En |
| AGROVOC Term: | RIVERS |
| AGROVOC Term: | WATER QUALITY |
| AGROVOC Term: | GEOGRAPHICAL INFORMATION SYSTEMS |
| AGROVOC Term: | LAND USE |
| AGROVOC Term: | SPATIAL DISTRIBUTION |
| AGROVOC Term: | WATER RESOURCES |
| AGROVOC Term: | WATER MANAGEMENT |
| AGROVOC Term: | INDONESIA |
| Geographical Term: | MALAYSIA |
| Depositing User: | Ms. Norfaezah Khomsan |
| Last Modified: | 24 Apr 2025 05:27 |
| URI: | http://webagris.upm.edu.my/id/eprint/16081 |
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