Geostatistics and hybrid particle swarm-simulated annealing optimization in rain gauges network simulation
In designing an effective and economic hydraulic structure for flood control, an optimal design of rain gauge network is important as it produces fast, accurate and important rainfall data. In this paper, geostatistical method integrated with hybrid of particle swarm optimization-simulated annealing...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Universiti Malaysia Pahang
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/26074/1/71.%20Geostatistics%20and%20hybrid%20particle%20swarm-simulated%20annealing.pdf http://umpir.ump.edu.my/id/eprint/26074/2/71.1%20Geostatistics%20and%20hybrid%20particle%20swarm-simulated%20annealing.pdf http://umpir.ump.edu.my/id/eprint/26074/ |
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| Institution: | Universiti Malaysia Pahang |
| Language: | English English |
| Summary: | In designing an effective and economic hydraulic structure for flood control, an optimal design of rain gauge network is important as it produces fast, accurate and important rainfall data. In this paper, geostatistical method integrated with hybrid of particle swarm optimization-simulated annealing is used to simulate the optimal locations and number of raingauges station. The simulation process used different generated rainfall data based on real rainfall data. The rainfall data randomly generated based on the exponential semivariogram model and it showed similar characteristics with the mean and standard deviation that is almost the same with real rainfall data. The proposed method successfully obtained the optimal number of rain gauges despite different sets of generated rainfall data. This situation shows that the proposed method is adequate to be applied in another case study, in other places or different data. |
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