Deskripsi Lengkap
| Sumber Pengatalogan : | LibUI eng rda |
| ISSN : | 21681015 |
| Majalah/Jurnal : | Journal of Industrial and Production Engineering |
| Volume : | Vol. 34, No. 7, Oktober 2017: Hal. 520 - 528 |
| Tipe Konten : | text (rdacontent) |
| Tipe Media : | unmediated (rdamedia) |
| Tipe Carrier : | volume (rdacarrier) |
| Akses Elektronik : | |
| Institusi Pemilik : | Universitas Indonesia |
| Lokasi : | Perpustakaan UI, Lantai 4, R. Koleksi Jurnal |
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| No. Panggil | No. Barkod | Ketersediaan |
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| 658 JIPE | 03-18-376651584 | TERSEDIA |
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Abstrak
ABSTRAK
This paper proposes methods for forward and inverse system modeling using Bayesian and least squares regression. This methods are based on both space-filling design criteria for multiple response problems and linear optimality criteria focusing on D optimality. Modeling with and without the constant term is considered motivated by the case study application of genetic network modeling. We propose extended one-factor-at-a-time experimentation followed bye augmentation of next stage design which offers biologists simplicity. Result are illustrated both numerical examples, a test problem from the literature, and a case study motivated by an real world biological research related to genetic network modeling.
This paper proposes methods for forward and inverse system modeling using Bayesian and least squares regression. This methods are based on both space-filling design criteria for multiple response problems and linear optimality criteria focusing on D optimality. Modeling with and without the constant term is considered motivated by the case study application of genetic network modeling. We propose extended one-factor-at-a-time experimentation followed bye augmentation of next stage design which offers biologists simplicity. Result are illustrated both numerical examples, a test problem from the literature, and a case study motivated by an real world biological research related to genetic network modeling.