Artikel Jurnal :: Kembali

Artikel Jurnal :: Kembali

Heating load predictions using the static neural networks method

Hwataik Han (Faculty of Engineering, Universitas Indonesia, 2015)

 Abstrak

Heating load calculations are essential to optimize energy use in buildings during the winter season. Instantaneous heating loads are determined by the outdoor weather conditions. It is intended to develop a method to predict instantaneous building heating loads, depending on various combinations of current input parameters so as to apply HVAC equipment operations. Heating loads have been calculated in a representative apartment building for one month in Seoul using Energy Plus. The datasets obtained are used to train artificial neural networks. Dry bulb temperature, dew point temperature, global horizontal radiation, direct normal radiation and wind speed are selected as the input parameters for training, while heating loads are the output. The design of experiments is used to investigate the effect of individual input parameters on the heating loads. The results of this study show the feasibility of using a machine learning technique to predict instantaneous heating loads for optimal building operations.

 Metadata

Jenis Koleksi : Artikel Jurnal
No. Panggil : UI-IJTECH 6:6 (2015)
Entri utama-Nama orang :
Subjek :
Penerbitan : Depok: Faculty of Engineering, Universitas Indonesia, 2015
Sumber Pengatalogan : LibUI eng rda
ISSN : 20869614
Majalah/Jurnal : International Journal of Technology
Volume : Vol. 6, No. 6, December 2015: Hal. 946-953
Tipe Konten : text
Tipe Media : unmediated
Tipe Carrier : volume
Akses Elektronik : https://doi.org/10.14716/ijtech.v6i6.1902
Institusi Pemilik : Universitas Indonesia
Lokasi : Perpustakaan UI, Lantai 4 R. Koleksi Jurnal
  • Ketersediaan
  • Ulasan
  • Sampul
No. Panggil No. Barkod Ketersediaan
UI-IJTECH 6:6 (2015) 08-23-42101215 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 9999920521968
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