Artikel Jurnal :: Kembali

Artikel Jurnal :: Kembali

Improvement of PM-10 Forecast using ANFIS model with an integrated hotspots / Rati Wongsathan.

Rati Wongsathan; (Thammasat University, 2018)

 Abstrak

ABSTRAK
Due to the situation of increasingly severe PM-10 pollution that adverse affects on humans and environment across the globe, the purpose of this work is to implement the optimal PM-10 forecast model as a basis tool in process of planing/controlling air pollution and public awareness apply to Chiang Mai city and surrounding area, in Northern Thailand. Accurate and reliable forecasting model are our goal. Due to the fuzzy feature of PM-10 as well as the high correlated hotspot during open burning and forest fires season of this study area, the adaptive neuro-fuzzy inference system (ANFIS)-based forecasting model has been statistically implemented as tool for daily mean PM-10 concentration estimation. For achieving more efficient and realistic model, the hotspot count among other meteorological parameters is utilized as the exogenous variable through the design and optimization. The forecasting performance evaluated in terms of the tradeoff between accuracy with regard to RMSE and MAE, computational complexity with respect to the multiplications per an execution, and reliablity through Akaike criterion information (AIC) is used to assess the forecast models. As forecasting results, the proposed ANFIS model with an integrated hotspots outperforms the other existing models.

 Metadata

Jenis Koleksi : Artikel Jurnal
No. Panggil : 607 STA 23:3 (2018)
Entri utama-Nama orang :
Subjek :
Penerbitan : Pathum Thani: Thammasat University, 2018
Sumber Pengatalogan : LibUI eng rda
ISSN : 25869000
Majalah/Jurnal : Science & Technology ASIA
Volume : Vol. 23, Jul-Sep 2018: Hal. 61-70
Tipe Konten : text
Tipe Media : unmediated
Tipe Carrier : volume
Akses Elektronik :
Institusi Pemilik : Universitas Indonesia
Lokasi : Perpustakaan UI, Lantai 4, R. Koleksi Jurnale
  • Ketersediaan
  • Ulasan
  • Sampul
No. Panggil No. Barkod Ketersediaan
607 STA 23:3 (2018) 03-19-808717038 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 20487913
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