Library Automation and Digital Archive
LONTAR
Fakultas Ilmu Komputer
Universitas Indonesia

Pencarian Sederhana

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Call Number SEM-372
Collection Type Indeks Artikel prosiding/Sem
Title Extracting Fuzzy Rules and Parameters Using Particle Swarm Optimization for Rainfall Foorecasting.
Author Tirana Noor Fatyanosa, Gusti Ahmad Fanshuri Alfarisyi, Arief Andy Soebroto, Fatwa Ramdani, Wayan Firdaus Mahmudy.;
Publisher ICACSIS 2017 Internation Conference on Advances Computer Science and Information System. Hal 339-345
Subject Fuzzy takagi-sugento-kang; particle swarm optimization; rainfall forecasting.
Location
Lokasi : Perpustakaan Fakultas Ilmu Komputer
Nomor Panggil ID Koleksi Status
SEM-372 TERSEDIA
Tidak ada review pada koleksi ini: 47373
Abstract- This paper deals with rainfall forecasting using rainfall data which taken from Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) and Oceanic Nino Index (ONI) data from NOAA Satellite and information service for Karangploso district. This paper proposes a Fuzzy Takagi-Sugeno-Kang rules and parameters extracting from particle swarm optimization (PSO) for rainfall forecasting. The novel of fuzzy rules and parameters within the data. Therefore, we able to obtain better accuracy. The experiment results demonstrate that the proposed solution able to obtain better accuracy. These results have proved the robustness of the proposed solution.