| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000329958 |
| 005 | | 20241017155830 |
| 008 | | 181129s2017 ||| | | | eng d |
| 020 | |
▼a 9780438206175 |
| 035 | |
▼a (MiAaPQ)AAI10634861 |
| 035 | |
▼a (MiAaPQ)rpi:11167 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 660 |
| 100 | 1 |
▼a Howsmon, Daniel P. |
| 245 | 10 |
▼a Data-Driven Modeling for Uncertain Biological Systems. |
| 260 | |
▼a [S.l.] :
▼b Rensselaer Polytechnic Institute.,
▼c 2017 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2017 |
| 300 | |
▼a 184 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Advisers: Juergen Hahn |
| 502 | 1 |
▼a Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2017. |
| 520 | |
▼a Data-driven models couple any systems, statistical, or optimization-based model to a particular application area and model objective. These models can operate in the midst of large amounts of model uncertainty since they do not require fundament |
| 590 | |
▼a School code: 0185. |
| 650 | 4 |
▼a Chemical engineering. |
| 650 | 4 |
▼a Biomedical engineering. |
| 690 | |
▼a 0542 |
| 690 | |
▼a 0541 |
| 710 | 20 |
▼a Rensselaer Polytechnic Institute.
▼b Chemical Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0185 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2017 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996666
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |