Analisis Komponen Utama (PCA) Suatu Cara untuk Menentukan Parameter Paling Berpengaruh dan Data Observasi Unik pada Ketel  

Oleh:

Elvayandri ; Pandjaitan, Lanny W.

Jenis: Article from Journal - ilmiah nasional - tidak terakreditasi DIKTI - atma jaya
Dalam koleksi: Metris: Jurnal Mesin, Elektro, Industri dan Sains vol. 1 no. 3 (Sep. 2000), page 9-16.
Topik: pca; PCA; Principal Component Analysis
Fulltext: Analisis.pdf (5.52MB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: MM42.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The, Principal Component Analysis (PCA) is carried Out to determine principal parameters. The PCA will reduce the data observation size, but has the smallest risk of the loosing information because only the significant data duplication will be excluded Using the unique and optimum data, the model of a system will be simpler and accurate built. This paper proposes the PCA for determine the optimum data observations. The PCA is applied to find the optimum data from the operation of a steam boiler (one of the dynamic systems) that has 14 parameters and 3958 data observations.

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