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of 60
pro vyhledávání: '"Kittipiyakul, Somsak"'
Autor:
Kittipiyakul, Somsak.
Publikováno v:
Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses
Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed September 12, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 214-220).
Title from first page of PDF file (viewed September 12, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 214-220).
Externí odkaz:
http://wwwlib.umi.com/cr/ucsd/fullcit?p3320077
Autor:
Sankalpa, Chatum1,2 (AUTHOR), Kittipiyakul, Somsak1 (AUTHOR) somsak@siit.tu.ac.th, Laitrakun, Seksan1 (AUTHOR)
Publikováno v:
Energies (19961073). Nov2022, Vol. 15 Issue 22, p8567. 30p.
Autor:
Kittipiyakul, Somsak
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (p. 99-100).
by Somsak Kittipiyakul.
M.Eng.
Includes bibliographical references (p. 99-100).
by Somsak Kittipiyakul.
M.Eng.
Externí odkaz:
http://hdl.handle.net/1721.1/39082
In this paper, a many-sources large deviations principle (LDP) for the transient workload of a multi-queue single-server system is established where the service rates are chosen from a compact, convex and coordinate-convex rate region and where the s
Externí odkaz:
http://arxiv.org/abs/0902.4569
This work analyzes the high-SNR asymptotic error performance of outage-limited communications with fading, where the number of bits that arrive at the transmitter during any time slot is random but the delivery of bits at the receiver must adhere to
Externí odkaz:
http://arxiv.org/abs/0809.1039
Publikováno v:
Applied System Innovation (ASI); Dec2023, Vol. 6 Issue 6, p100, 29p
Publikováno v:
Designs; Dec2022, Vol. 6 Issue 6, p99, 21p
Autor:
Chapagain Kamal, Kittipiyakul Somsak
Publikováno v:
MATEC Web of Conferences, Vol 55, p 06003 (2016)
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for modelling and forecasting a day ahead electricity load. AR(2) is used to show the dependency of next data on its previous two days data because the nature
Externí odkaz:
https://doaj.org/article/c6dbaff488464eefaabff16068435349
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