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Performance Estimation (performance + estimation)

Distribution by Scientific Domains
Engineering75%

Selected Abstracts

SIMPERF: SIMULINK-based educational software for vehicle's performance estimation

COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, Issue 2 2009
J. A. Calvo
Abstract This paper presents an educational software called SIMPERF developed to allow the engineering students to learn easily and quickly about the vehicle's performance calculations. This software uses the SIMULINK library of MATLAB which has shown to be a good choice to implement and solve the implicated equations. The model allows us to achieve the vehicle's performances with enough accuracy and to modify the parameters than influence on these performances quickly and easily in order to understand the physic phenomena involved. © 2008 Wiley Periodicals, Inc. Comput Appl Eng Educ 17: 139,147, 2009; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae20191 [source]

Investigation into the performance of a micro gravitational heat pipe and a micro gravitational heat pipe with artery

INTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 1 2003
S.B. Riffat
Abstract The performance of a normal micro gravitational heat pipe was investigated using the analytical and numerical models previously developed. An innovative structure of the heat pipe, i.e. the micro gravitational heat pipe with artery, was then proposed in an attempt to overcome some of the drawbacks of the normal pipe. The thermal behaviour of the new type of heat pipe was simulated, and this was compared with that of a normal micro heat pipe. A performance estimation of both pipes was carried out based on the simulation results. Copyright © 2002 John Wiley & Sons, Ltd. [source]

RANDOM APPROXIMATED GREEDY SEARCH FOR FEATURE SUBSET SELECTION

ASIAN JOURNAL OF CONTROL, Issue 3 2004
Feng Gao
ABSTRACT We propose a sequential approach called Random Approximated Greedy Search (RAGS) in this paper and apply it to the feature subset selection for regression. It is an extension of GRASP/Super-heuristics approach to complex stochastic combinatorial optimization problems, where performance estimation is very expensive. The key points of RAGS are from the methodology of Ordinal Optimization (OO). We soften the goal and define success as good enough but not necessarily optimal. In this way, we use more crude estimation model, and treat the performance estimation error as randomness, so it can provide random perturbations mandated by the GRASP/Super-heuristics approach directly and save a lot of computation effort at the same time. By the multiple independent running of RAGS, we show that we obtain better solutions than standard greedy search under the comparable computation effort. [source]

EST Adaptive optics performance estimations

ASTRONOMISCHE NACHRICHTEN, Issue 6 2010
T. Berkefeld
Abstract We give a short overview of the Adaptive Optics (AO) and Multi-conjugate Adaptive Optics (MCAO) system of the planned 4 m European Solar Telescope (EST). The optimization process of the AO / MCAO parameters is shown, including the parameters and layout of the Shack-Hartmann wavefront sensor setup and the DMs. We show the expected performance of the AO and MCAO system (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]