Audah, Haidar and Ir. Widandi Soetopo,, M.Eng. and Prof. Dr. Ir. Lily Montarcih L.,, M.Sc. (2018) Analisis Model Tangki Dengan Metode Algoritma Genetik Sub Daerah Aliran Sungai Andagile Hulu Di Kabupaten Gorontalo Utara. Magister thesis, Universitas Brawijaya.
Abstract
Algoritma Genetik (AG) merupakan salah satu metode yang cukup handal untuk pencarian parameter-parameter optimal. Pembahasan dalam penelitian ini difokuskan untuk mengetahui simulasi Model Tangki Susunan Seri, Susunan Paralel dan Susunan Gabungan pada lokasi studi. Hasil penelitian pada Sub DAS Andagile Hulu menunjukkan bahwa simulasi model tangki menggunakan metode Algoritma Genetik terbukti meningkatkan kinerja debit hasil bangkitan, ditunjukkan dengan nilai RMSE yang lebih kecil daripada simulasi model tangki menggunakan metode Trial and Error. Namun debit simulasi yang dihasilkan, masih terlihat berbeda dengan seri debit aktual. Perbedaan ini bisa disebabkan karena asumsi awal dari parameter-parameter yang menjadi generasi awal genethic algorithm belum disesuaikan dengan kondisi tata guna lahan, kondisi jenis tanah, kondisi morfometri sungai, kondisi ketinggian, kondisi geologi di lokasi studi. Susunan tangki gabungan 2-2 lebih efektif dalam memodelkan debit di lokasi tersebut. Dengan indikator nilai RMSE 0.093 untuk simulasi trial and error dan 0.050 untuk optimasi algoritma genetik
English Abstract
Genetic Algorithm is a reliable method for finding optimal parameters. The discussion in this study focused on knowing the simulation of the Tank Model Series, Parallel and Combined at location. The results of the research on Andagile Hulu showed that the simulation of the tank model using the Genetic Algorithm method was proven to improve the performance of the generated discharge, indicated by the RMSE value which was smaller than the simulation of the tank model using the Trial and Error method. But the simulation discharge generated, still looks different from the actual discharge series. This difference can be caused the initial assumption of the parameters that became the initial generation of the genethic algorithm has not been adjusted to the conditions of land use, soil type conditions, river morphometry conditions, altitude conditions, geological conditions at the study location. The composition of the combined tank 2-2 is more effective in modeling the discharge at that location. With the indicator value RMSE 0.093 for trial and error simulation and 0.050 for genetic algorithm optimization
Other obstract
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| Item Type: | Thesis (Magister) |
|---|---|
| Identification Number: | TES/005.1/FT/a/2018/041809181 |
| Uncontrolled Keywords: | model tangki, trial and error, algoritma genetik, tank model, trial and error, genetic algorithm |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data > 005.1 Programming |
| Divisions: | S2/S3 > Magister Teknik Pengairan, Fakultas Teknik |
| Depositing User: | Nur Cholis |
| Date Deposited: | 12 Aug 2022 07:44 |
| Last Modified: | 12 Aug 2022 07:44 |
| URI: | http://repository.ub.ac.id/id/eprint/193197 |
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