parameter
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MECHNICAL TECHNOLOGY PARAMETER - 图文
TRANSFERGEOMETRICA L DATAFROM CAD
ONLY MAIN CONTOURDIMENSIONED
NON-DIMENSIONED RADII R= X
GEOMETRIE AUS CAD UEBERNEHMEN
NUR HAUPTKONTUR BEMASST
NICHIT BEMASSTE RADIEN R = X
BLACKENING BRUENIRET
BURR-FREE GRATFREI
XXX=JAL IDENT NO MARKED ON PART XXX=ZEICHNUNGS-NR UNVERLIERBAR
TOOL XXXX
WENKZEUG XXXX
CASE HARDEN TO XX ±2 HRC.DEPTH OF CASE 0.5MM EINSATZGEHAERTET XX ±2 HRC.EHT 0.2 MM
FLANE HARDEN XX ±2 HRC
FANMMENGEHAERTET XX ±2 HRC
STRESS –RELIEVE
SPANNUNGSARM GEGLVEHT
GAS NITRIDE TO XXX ±50 HV.DEPTH OF CAS
Stochastic convergence analysis and parameter selection of the standard particle swarm optimization
粒子群优化
InformationProcessingLetters102(2007)
8–16
/locate/ipl
Stochasticconvergenceanalysisandparameterselectionofthestandardparticleswarmoptimizationalgorithm
M.Jiang ,Y.P.Luo,S.Y.Yang
DepartmentofAutomation,TsinghuaUniversity,Beijing100084,ChinaReceived18January2006;receivedinrevisedform20October2006
Availableonline17November2006CommunicatedbyF.MeyeraufderHeide
Abstract
Thisletterpresentsaformalstochasticconvergenceanalysisofthestandardparticleswarmoptimization(PSO)algorithm,whichinvolveswithrandomness.Byregardingeachparticle’sposi
Parameter Preserving Model Reduction for MEMS System-level Simulation and Design
Abstract. Model reduction is a very helpful tool to generate compact models for system-level simulation. Quite often however, system matrices depend on design parameters and the new goal is not only to reduce the original system but also to preserve system
Parameter Preserving Model Reduction for MEMS System-level Simulation and Design
E. B. Rudnyi, C. Moosmann, A. Greiner, T. Bechtold, J. G. Korvink
IMTEK, Freiburg University, Germany
Corresponding Author: J. G. Korvink
Lab of Simulation, Department of Microsystems Engineering