MARC보기
LDR01669nam u200481 4500
001000000467493
00520220223112719
008220131s2020 us ||||||||||||||c||eng d
020 ▼a 9798492742102
035 ▼a (MiAaPQ)AAI28264168
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 720
1001 ▼a Xu, Yujie.
24510 ▼a Using Machine Learning to Target Retrofits in Commercial Buildings under Alternative Climate Change Scenarios.
260 ▼a [S.l.]: ▼b Carnegie Mellon University., ▼c 2020.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2020.
300 ▼a 216 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
500 ▼a Advisor: Loftness, Vivian V.
5021 ▼a Thesis (Ph.D.)--Carnegie Mellon University, 2020.
506 ▼a This item must not be sold to any third party vendors.
590 ▼a School code: 0041.
650 4 ▼a Architectural engineering.
650 4 ▼a Energy.
650 4 ▼a Climate change.
650 4 ▼a Information science.
690 ▼a 0462
690 ▼a 0791
690 ▼a 0404
690 ▼a 0723
71020 ▼a Carnegie Mellon University. ▼b Architecture.
7730 ▼t Dissertations Abstracts International ▼g 83-05B.
773 ▼t Dissertation Abstract International
790 ▼a 0041
791 ▼a Ph.D.
792 ▼a 2020
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T16051171 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202202 ▼f 2022
990 ▼a ***1012033
991 ▼a E-BOOK