Bat algorithm and neural network for monthly streamflow prediction

Nuratiah Zaini, Marlinda Abdul Malek, Marina Yusoff, Siti Fatimah Che Osmi, Nurul Hani Mardi, Shuhairy Norhisham @ Masam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Streamflow prediction has a significance influence on improving water supply management and flood prevention. The applications of artificial intelligence (AI) have been proved to have better performance as compared to conventional statistical method in streamflow prediction. Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). BA is an optimization technique, which is to optimize BPNN in deciding optimum parameters and then improve the prediction accuracy. The study area chosen is Kuantan river and Kenau river, located in Kuantan, Malaysia. Two prediction models are proposed in this study which are BPNN and hybrid Bat-BPNN. Monthly historical rainfall data, antecedent river flow data and meteorology parameters data for two different rivers were used as the input to the proposed models. The performance of the proposed prediction models for Kuantan river and Kenau river are then being compared and evaluated in term of RMSE and R2. It is found that hybrid model, Bat-BPNN yields lower RMSE and provides higher R2 as compared to BPNN model at both Kuantan river and Kenau river. Therefore, it can be concluded that, proposed hybrid model yields better performances as compared to BPNN model for monthly streamflow prediction.

Original languageEnglish
Title of host publicationGreen Design and Manufacture
Subtitle of host publicationAdvanced and Emerging Applications: Proceeding of the 4th International Conference on Green Design and Manufacture 2018
EditorsMuhammad Faheem Bin Mohd Tahir, Romisuhani Ahmad, Mohd Nasir Bin Mat Saad, Mohd Fathullah Bin Ghazli, Mohd Mustafa Al-Bakri Abdullah, Shayfull Zamree Bin Abd. Rahim, Liyana Binti Jamaludin
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417526
DOIs
Publication statusPublished - 09 Nov 2018
Event4th International Conference on Green Design and Manufacture 2018, IConGDM 2018 - Ho Chi Minh, Viet Nam
Duration: 29 Apr 201830 Apr 2018

Publication series

NameAIP Conference Proceedings
Volume2030
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

Other4th International Conference on Green Design and Manufacture 2018, IConGDM 2018
CountryViet Nam
CityHo Chi Minh
Period29/04/1830/04/18

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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    Zaini, N., Abdul Malek, M., Yusoff, M., Osmi, S. F. C., Mardi, N. H., & Norhisham @ Masam, S. (2018). Bat algorithm and neural network for monthly streamflow prediction. In M. F. B. M. Tahir, R. Ahmad, M. N. B. M. Saad, M. F. B. Ghazli, M. M. A-B. Abdullah, S. Z. B. A. Rahim, & L. B. Jamaludin (Eds.), Green Design and Manufacture: Advanced and Emerging Applications: Proceeding of the 4th International Conference on Green Design and Manufacture 2018 [020260] (AIP Conference Proceedings; Vol. 2030). American Institute of Physics Inc.. https://doi.org/10.1063/1.5066901