CD Skripsi

Model Hidrologi Runtun Waktu Untuk Peramalan Debit Sungai Menggunakan Metode Gabungan Transformasi Wavelet – Artificial Neural Network (Studi Kasus : Sub Das Siak Bagian Hulu)

---

Softcomputing method has been widely used as hydrological analysis model, one of them for streamflow forecasting. Hybrid model of Wavelet Transformation - Artificial Neural Network (WANN) is one of a softcomputing method that can be used to predict streamflow. WANN models need to be tested reliability of the Siak Hulu sub-watershed given the importance of streamflow information to generate management, planning, and useing water resources and sustainable accurately.
WANN models in this study used AWLR data converted into discharge data at Siak Hulu sub-watershed from January 2002 to December 2012. First, the data were decomposed and reconstructed using Wavelet Transformation. Then, ANN constructed forecasting model use backpropagation algorithm. WANN models were constructing use 12 forecasting scheme, and then it compared to obtain the best model of each forecasting scheme.
The results of statistical analysis on coefficient of correlation (R) showed that the 12 schemes of WANN models developed by the process of calibration, testing, validation and simulation were categorized as very strong correlation. As for the process simulation models from 2011 to 2012, WANN models db5 level 2 for lead time one day scheme resulted the best correlation coefficient (R) is 0.9501752.
Keywords: forecasting streamflow, Siak sub-watershed, Wavelet Transformation, ANN.

---

Ketersediaan

Informasi Detail

Judul Seri

-

No. Panggil

07 01. 115 (0069)

Penerbit

Pekanbaru : Universitas Riau - Fakultas Teknik - Teknik Sipil., 2015

Deskripsi Fisik

xviii, 70 hlm.:ill,; 29 cm

Bahasa

ISBN/ISSN

-

Klasifikasi

07 01. 115 (0069)

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

-

Info Detail Spesifik

-

Pernyataan Tanggungjawab

DAUS

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar