超星 - Test 6 - 查题吧

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Whichofthefollowingalgorithmsareevolutionaryalgorithms?

A. antcolonyoptimization(ACO)
B. bacterialcolonyoptimization
C. swarm intelligence
D. genetic algorithm

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Enabling technologies in synthetic biology include:

A. standardized parts
B. synthesis: e.g. DNA, chromosome & genome synthesis & editing
C. sequencing
D. microfluidics, modular protein assembly, & modeling

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Whichofthefollowingalgorithmsareevolutionaryalgorithms?

A. immunegeneticalgorithm
B. multi-populationquantumevolutionary
C. geneticprogramming
D. cooperativecoevolutionaryalgorithm

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Biological parts suitable for synthetic modifications are:

A. synthetic DNA based parts & genomes
B. synthetic RNA based parts
C. synthetic amino acids
D. synthetic proteins

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Whichofthefollowingalgorithmsareevolutionaryalgorithms?

A. cooperative-competitive genetic algorithm
B. evolutionary clustering algorithm
C. micro-genetic algorithm
D. solution-annealing genetic algorithm

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Antcolonyoptimization(ACO)

Antcolonyoptimization(ACO)isaprobabalistic(stochastic),heuristicoptimizationtechniqueinspiredbythewayantsmake&findpathsfromthecolonytofood.Thetechniqueisusedtosolvediscreteoptimizationproblemsthatcanbereducedtofindinggoodpathsthroughgraphs.ThefirstappearanceofanACOsystemwasinaPhDthesisin1992byMarcoDorigoatPolitecnicodiMilano.ItwascalledAntSystem(AS).Since1995variousotherextendedversionsofAShavebeendeveloped,includingAntColonySystem(ACS)andMAX-MINAntSystem(MMAS).In1999DorigoproposedtheACOmetaheuristicthatbecamethemostsuccessfulandrecognizedalgorithmbasedonantbehavior.
B. Whenoneantfindsanoptimalpathfromthecolonytoafoodsource,otherantsaremorelikelytofollowthatpath&positivefeedbackeventuallycausesalltheantstofollowthesamepath.TheACOalgorithmmimicsthisbywalkingaroundthegraphrepresentingtheproblemtosolve.Thesealgorithmshavebeenappliedtothesymmetric&asymmetrictravelingsalesmanproblemwithnear-optimalresults.
C. TherehasbeenaninterestinusingACOfornetworkrouting&urbantransportationsystemssincethealgorithmcanberuncontinuouslygivingittheabilitytoadapttochangesinrealtime.Thisisanadvantageoverthesimulatedannealing&geneticalgorithmapproachessincetheydonotchangedynamically.
D. Inmachinelearning&dataminingproblems,ACOvariationshavebeenusedtocreateamodelofthewayworkerants"cluster"antcorpsesinantcemetarymaintenance.Thishasbeenappliedtoataskcalledclusteringinmachinelearningwhichinvolvesfindinggroupsofobjectsthataresimilar.Thismethodhasproventohavehigherperformance&accuracythanpreviousclassicalmethods.

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