3 Hours flood water level prediction using NNARX structure: Case study Kuala Lumpur

Research output: ResearchConference contribution

Abstract

Nowadays flood water level predictions have become one of the most popular subject matter among researcher because this natural disaster damages people's life and property. In addition, flood is also one of the natural disasters that occur frequently around the world. However, since the dynamic of the flood itself is highly nonlinear, it is a very difficult task to predict the flood water level ahead of time. Therefore, since Multilayer Perceptron Neural Network is widely known to solve nonlinear cases, this paper proposed a 3 hours flood water level prediction for Kuala Lumpur flood prone using advance Neural Network technique. All samples used in model development and testing stage were real-time samples obtained from Department of Irrigation and Drainage Malaysia upon special request. The 3 hours NNARX flood water level prediction model have been successfully developed, analyzed and tested using MATLAB Neural Network Toolbox. Results show that the NNARX model successfully predicted flood water level 3 hours ahead of time.

LanguageEnglish
Title of host publicationProceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages53-56
Number of pages4
ISBN (Electronic)9781509050895
DOIs
StatePublished - Feb 15 2017
Externally publishedYes
Event6th International Conference on System Engineering and Technology, ICSET 2016 - Bandung, Indonesia
Duration: Oct 3 2016Oct 4 2016

Other

Other6th International Conference on System Engineering and Technology, ICSET 2016
CountryIndonesia
CityBandung
Period10/3/1610/4/16

Fingerprint

water level
prediction
Water levels
Neural networks
natural disaster
Disasters
irrigation
drainage
damage
development model
world
Multilayer neural networks
Irrigation
MATLAB
Drainage
Testing

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Media Technology
  • Water Science and Technology

Cite this

Ruslan, F. A., Samad, A. M., & Adnan, R. (2017). 3 Hours flood water level prediction using NNARX structure: Case study Kuala Lumpur. In Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016 (pp. 53-56). [7857537] Institute of Electrical and Electronics Engineers Inc.. DOI: 10.1109/FIT.2016.7857537

3 Hours flood water level prediction using NNARX structure : Case study Kuala Lumpur. / Ruslan, Fazlina Ahmat; Samad, Abd Manan; Adnan, Ramli.

Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 53-56 7857537.

Research output: ResearchConference contribution

Ruslan, FA, Samad, AM & Adnan, R 2017, 3 Hours flood water level prediction using NNARX structure: Case study Kuala Lumpur. in Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016., 7857537, Institute of Electrical and Electronics Engineers Inc., pp. 53-56, 6th International Conference on System Engineering and Technology, ICSET 2016, Bandung, Indonesia, 10/3/16. DOI: 10.1109/FIT.2016.7857537
Ruslan FA, Samad AM, Adnan R. 3 Hours flood water level prediction using NNARX structure: Case study Kuala Lumpur. In Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016. Institute of Electrical and Electronics Engineers Inc.2017. p. 53-56. 7857537. Available from, DOI: 10.1109/FIT.2016.7857537
Ruslan, Fazlina Ahmat ; Samad, Abd Manan ; Adnan, Ramli. / 3 Hours flood water level prediction using NNARX structure : Case study Kuala Lumpur. Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 53-56
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