bibtype C - Conference Paper (international conference)
ARLID 0393327
utime 20240103202652.4
mtime 20130627235959.9
DOI 10.1007/978-3-319-00551-5_33
title (primary) (eng) Trajectory Optimization under Changing Conditions through Evolutionary Approach and Black-Box Models with Refining
specification
page_count 8 s.
media_type P
serial
ARLID cav_un_epca*0393326
ISBN 978-3-319-00550-8
title Distributed Computing and Artificial Intelligence
part_num XVIII
part_title Advances in Intelligent Systems and Computing
page_num 267-274
publisher
place Cham
name Springer
year 2013
keyword Empirical function minimization
keyword black-box modeling
keyword simplification
keyword refining
keyword dynamic building control
author (primary)
ARLID cav_un_auth*0292010
name1 Macek
name2 Karel
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
institution UTIA-B
share 90
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0292027
name1 Rojíček
name2 J.
country CZ
author
ARLID cav_un_auth*0052682
name1 Bičík
name2 V.
country CZ
source
url http://library.utia.cas.cz/separaty/2013/AS/macek-trajectory optimization under changing.pdf
cas_special
abstract (eng) This article provides an algorithm that is dedicated to repeated trajectory optimization with a fixed horizon and addresses processes that are difficult to describe by the established laws of physics. Typically, soft-computing methods are used in such cases, i.e. black-box modeling and evolutionary optimization. Both suffer from high dimen- sions that make the problems complex or even computationally infeasble. We propose a way how to start from very simple problems and - after the simple problems are covered sufficiently - proceed to more complex ones. We provide also a case study related to the dynamic optimization of the HVAC (heating, ventilation, and air conditioning) systems.
action
ARLID cav_un_auth*0292011
name 10th International Symposium on Distributed Computing and Artificial Intelligence
place Salamanca
dates 22.05.2013-24.05.2013
country ES
reportyear 2014
RIV BB
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0222068
arlyear 2013
mrcbU63 cav_un_epca*0393326 Distributed Computing and Artificial Intelligence Advances in Intelligent Systems and Computing XVIII 978-3-319-00550-8 267 274 Distributed Computing and Artificial Intelligence Cham Springer 2013 217 XVIII