人工智能英语教程参考试卷

参考试卷

一、写出以下单词的中文意思（每小题0.5分，共10分）

1accuracy11customize

2actuator12definition

3adjust13defuzzification

4agent14deployment

5algorithm15effector

6analogy16entity

7attribute17extract

8backtrack18feedback

9blockchain19finite

10cluster20framework

二、根据给出的中文意思，写出英文单词（每小题0.5分，共10分）

1V.收集，搜集11n.神经元；神经细胞

2adj.嵌入的，内置的12n.节点

3n.指示器；指标13V.运转；操作

4n.基础设施，基础架构14n.模式

5V.合并：集成15V.察觉，发觉

6n.解释器，解释程序16n.前提

7n.迭代；循环17adj.程序的；过程的

8n.库18n.回归

919adj.健壮的，强健的;

n.元数据

结实的

10v.监视；控制；监测20V.筛选

三、根据给出的短语，写出中文意思（每小题1分，共10分）

1dataobject

2cybersecurity

3smartmanufacturing

4clusteredsystem

5datavisualization

6opensource

7analyzetext

8cloudcomputing

9computationpower

10objectrecognition

四、根据给出的中文意思，写出英文短语（每小题1分，共10分）

1数据结构______________________

2决策树______________________

3演绎推理______________________

4贪婪最佳优先搜索______________________

5隐藏模式，隐含模式______________________

6知识挖掘______________________

7逻辑推理______________________

8预测性维护______________________

9搜索引擎______________________

10文本挖掘技术

五、写出以下缩略语的完整形式和中文意思（每小题1分，共10分）

缩略语_______________完整形式中文意思___________

1ANN

2AR

3BFS

4CV

5DFS

6ES

7IA

8KNN

9NLP

10VR

六、阅读短文，回答问题(每小题2分，共10分)

ArtificialNeuralNetwork(ANN)

Anartificialneuralnetwork(ANN)isthepieceofacomputingsystemdesignedtosimulate

thewaythehumanbrainanalyzesandprocessesinformation.Itisthefoundationofartificial

intelligence(AI)andsolvesproblemsthatwouldproveimpossibleordifficultbyhumanor

statisticalstandards.ANNshaveself-learningcapabilitiesthatenablethemtoproducebetter

resultsasmoredatabecomesavailable.

Artificialneuralnetworksarebuiltlikethehumanbrain,withneuronnodesinterconnected

likeaweb.Thehumanbrainhashundredsofbillionsofcellscalledneurons.Eachneuronismade

upofacellbodythatisresponsibleforprocessinginformationbycarryinginformationtowards

(inputs)andaway(outputs)fromthebrain.

AnANNhashundredsorthousandsofartificialneuronscalledprocessingunits,whichare

interconnectedbynodes.Theseprocessingunitsaremadeupofinputandoutputunits.Theinput

unitsreceivevariousformsandstructuresofinformationbasedonaninternalweightingsystem,

andtheneuralnetworkattemptstolearnabouttheinformationpresentedtoproduceoneoutput

report.Justlikehumansneedrulesandguidelinestocomeupwitharesultoroutput,ANNsalso

useasetoflearningrulescalledbackpropagation,anabbreviationfbrbackwardpropagationof

error,toperfecttheiroutputresults.

AnANNinitiallygoesthroughatrainingphasewhereitlearnstorecognizepatternsindata,

whethervisually,aurally,ortextually.Duringthissupervisedphase,thenetworkcomparesits

actualoutputproducedwithwhatitwasmeanttoproduce—thedesiredoutput.Thedifference

betweenbothoutcomesisadjustedusingbackpropagation.Thismeansthatthenetworkworks

backward,goingfromtheoutputunittotheinputunitstoadjusttheweightofitsconnections

betweentheunitsuntil(hedifferencebetweentheactualanddesiredoutcomeproducesthelowest

possibleerror.

Aneuralnetworkmaycontainthefollowing3layers:

Inputlayer-Theactivityoftheinputunitsrepresentstherawinformationthatcanfeedinto

thenetwork.

Hiddenlayer-Todeterminetheactivityofeachhiddenunit.Theactivitiesoftheinputunits

andtheweightsontheconnectionsbetweentheinputandthehiddenunits.Theremaybeoneor

morehiddenlayers.

Outputlayer-Thebehavioroftheoutputunitsdependsontheactivityofthehiddenunits

andtheweightsbetweenthehiddenandoutputunits.

1.Whatisanartificialneuralnetwork(ANN)?

2.Whatiseachneuronmadeupof?

3.Whadotheinputunitsdo?

4.WhatdoesanANNinitiallygothrough?

5.Howmanylayersmayaneuralnetworkcontain?Whatarethey?

七、将下列词填入适当的位置(每词只用一次)。(每小题10分，共20分)

填空题1

供选择的答案:

transactionsinformationtechniquesfraudnodes

unstructuredsubsetsharedautomatedexplosion

DeepLearning

1.WhatIsDeepLearning?

Deeplearningisanartificialintelligence(AI)functionthatimitatestheworkingsofthe

humanbraininprocessingdataandcreatingpatternsforuseindecisionmaking.Deeplearningis

a___1___ofmachinelearninginartificialintelligencethathasnetworkscapableoflearning

unsupervisedfromdatathatis___2___orunlabeled.Alsoknownasdeepneurallearningordeep

neuralnetwork.

2.HowDoesDeepLearningWork?

Deeplearninghasevolvedhand-in-handwiththedigitalera,whichhasbroughtaboutan

___3___ofdatainallformsandfromeveryregionoftheworld.Thisdata,knownsimplyasbig

data,isdrawnfromsourceslikesocialmedia,internetsearchengines,e-commerceplatforms,and

onlinecinemas,amongothers.Thisenormousamountofdataisreadilyaccessibleandcanbe

___4___throughfintechapplicationslikecloudcomputing.

However,thedata,whichnormallyisunstructured,issovastthatitcouldtakedecadesfor

humanstocomprehenditandextractrelevant___5___.Companiesrealizetheincrediblepotential

thatcanresultfromunravelingthiswealthofinformationandareincreasinglyadaptingtoAI

systemsfor___6___support.

3.DeepLearningvs.MachineLearning

OneofthemostcommonAI___7___usedforprocessingbigdataismachinelearning,a

self-adaptivealgorithmthatgetsincreasinglybetteranalysisandpatternswithexperienceorwith

newlyaddeddata.

IfadigitalpaymentscompanywantedtodetecttheoccuiTenceorpotential___8___inits

system,itcouldemploymachinelearningtoolsforthispurpose.Thecomputationalalgorithm

builtintoacomputermodelwillprocessall___9___happeningonthedigitalplatform,find

patternsinthedataset,andpointoutanyanomalydetectedbythepattern.

Deeplearningutilizesahierarchicallevelofartificialneuralnetworkstocarryoutthe

processofmachinelearning.Theartificialneuralnetworksarebuiltlikethehumanbrain,with

neuron___10___connectedtogetherlikeaweb.Whiletraditionalprogramsbuildanalysiswith

datainalinearway,thehierarchicalfunctionofdeeplearningsystemsenablesmachinesto

processdatawithanonlinearapproach.

填空题2

供选择的答案:

storedresolutionmatchlookunlock

databasephotographeyesreturn,identifying

FaceRecognition

Facerecognitionsystemsusecomputeralgorithmstopickoutspecific,distinctivedetails

aboutaperson'sface.Thesedetails,suchasdistancebetweenthe___1___orshapeofthechin,

arethenconvertedintoamathematicalrepresentationandcomparedtodataonotherfaces

collectedinafacerecognitiondatabase.Thedataaboutaparticularfaceisoftencalledaface

templateandisdistinctfroma___2___becauseit'sdesignedtoonlyincludecertaindetailsthat

canbeusedtodistinguishonefacefromanother.

Somefacerecognitionsystems,insteadofpositively___3___anunknownperson,are

designedtocalculateaprobabilitymatchscorebetweentheunknownpersonandspecificface

templates___4___inthedatabase.Thesesystemswillofferupseveralpotentialmatches,ranked

inorderoflikelihoodofcorrectidentification,insteadofjustreturningasingleresult.

Facerecognitionsystemsvaryintheirabilitytoidentifypeopleunderchallengingconditions

suchaspoorlighting,lowqualityimage___5___,andsuboptimalangleofview(suchasina

photographtakenfromabovelookingdownonanunknownperson).

Whenitcomestoenors,therearetwokeyconceptstounderstand:

A<6falsenegative“iswhenthefacerecognitionsystemfailsto___6___matchaperson's

facetoanimagethatis,infact,containedinadatabase.Inotherwords,thesystemwill

erroneously___7___zeroresultsinresponsetoaquery.

A“falsepositive“iswhenthefacerecognitionsystemdoesmatchaperson'sfacetoan

imageina___8___,butthatmatchisactuallyincorrect.Thisiswhenapoliceofficersubmitsan

imageof"Joe,"butthesystemerroneouslytellstheofficerthatthephotoisof"Jack.”

Whenresearchingafacerecognitionsystem,itisimportantto___9___closelyatthe"false

positive“rateandthe“falsenegative^^rate,sincethereisalmostalwaysatrade-off.Forexample,

ifyouareusingfacerecognitionto___10___yourphone,itisbetterifthesystemfailstoidentify

youafewtimes(falsenegative)thanitisforthesystemtomisidentifyotherpeopleasyouand

letsthosepeopleunlockyourphone(falsepositive).Iftheresultofamisidentificationisthatan

innocentpersongoestojail(likeamisidentificationinamugshotdatabase),thenthesystem

shouldbedesignedtohaveasfewfalsepositivesaspossible.

六、将下面两篇短文翻译成中文(每小题10分，共20分)

短文1

DifferencesbetweenStrongAIandWeakAI

1.Meaning

StrongAIisatheoreticalformofartificialintelligencewhichsupportstheviewthat

machinescanreallydevelophumanintelligenceandconsciousnessinthesamewaythatahuman

inconscious.StrongAIreferstoahypotheticalmachinethatexhibitshumancognitiveabilities.

WeakAI(alsoknownasnarrowAI),ontheotherhand,isaformofartificialintelligencethat

referstotheuseofadvancedalgorithmstoaccomplishspecificproblemsolvingorreasoningtasks

thatdonotencompassthefullrangeofhumancognitiveabilities.

2.Functionality

FunctionsarelimitedinweakAIascomparedtostrongAI.WeakAIdoesnotachieve

self-awarenessordemonstrateawiderangeofhumancognitiveabilitiesthatahumanmayhave.

WeakAIreferstosystemsthatareprogrammedtoaccomplishawiderangeproblemsbutoperate

withinapre-determinedorpre-definedrangeoffunctions.StrongAI,ontheotherhand,refersto

machinesthatexhibithumanintelligence.Theideaistodevelopartificialintelligencetothepoint

wherehumaninteractwithmachinesthatareconscious,intelligentanddrivenbyemotionsand

self-awareness.

3.Goal

ThegoalofweakAIistocreateatechnologythatallowsallowsmachinesandcomputersto

toaccomplishspecificproblemsolvingorreasoningtasksatasignificantlyquickerpacethana

humancan.Butitdoesnotnecessarilyincorporateanyrealworldknowledgeabouttheworldof

theproblemthatisbeingsolved.ThegoalofstrongAIistodevelopartificialintelligencetothe

pointwhereitcanbeconsideredtruehumanintelligence.StrongAIisatypeofwhichdoesnot

existyetinitstrueform.

短文2

PatternRecognition

PatternRecognitionisdefinedastheprocessofidentifyingthetrends(globalorlocal)inthe

givenpattern.Apatterncanbedefinedasanythingthatfollowsatrendandexhibitssomekindof

regularity.Therecognitionofpatternscanbedonephysically,mathematicallyorbytheuseof

algorithms.Whenwetalkaboutpatternrecognitioninmachinelearning,itindicatestheuseof

powerfulalgorithmsforidentifyingtheregularitiesinthegivendata.Patternrecognitioniswidely

usedinthenewagetechnicaldomainslikecomputervision,speechrecognition,facerecognition,

etc.

Therearetwotypesofpatternrecognitionalgorithmsinmachinelearning.

1.SupervisedAlgorithms

Thepatternrecognitioninasupervisedapproachiscalledclassification.Thesealgorithms

useatwo-stagemethodologyforidentifyingthepatterns.Thefirststageisthedevelopment/

constructionofthemodelandthesecondstageinvolvesthepredictionforneworunseenobjects.

Thekeyfeaturesinvolvingthisconceptarelistedbelow.

•Classifythegivendataintotwosets-trainingsetandtestingset.

•TrainthemodelusingasuitablemachinelearningalgorithmsuchasSVM(SupportVector

Machines),decisiontrees,randomforest,etc.

•Themodelistrainedonthetrainingsetandtestedonthetestingset.

•Theperformanceofthemodelisevaluatedbasedoncorrectpredictionsmade.

2.UnsupervisedAlgorithms

Incontrasttothesupervisedalgorithmsforpatternmakeuseoftrainingandtestingsets,

thesealgorithmsuseagroupbyapproach.Theyobservethepatternsinthedataandgroupthem

basedonthesimilarityintheirfeaturessuchasdimensiontomakeaprediction.Let'ssaythatwe

haveabasketofdifferentkindsoffruitssuchasapples,oranges,pears,andcherries.Weassume

thatwedonotknowthenamesofthefruits.Wekeepthedataasunlabeled.Now,supposewe

encounterasituationwheresomeonecomesandtellsustoidentifyanewfruitthatwasaddedto

thebasket.Insuchacasewemakeuseofaconceptcalledclustering.

•Clusteringcombinesorgroupsitemshavingthesamefeatures.

•Nopreviousknowledgeisavailableforidentifyinganewitem.

•Theyusemachinelearningalgorithmslikehierarchicalandk-mansclustering.

,Basedonthefeaturesorpropertiesofthenewobject,itisassignedtoagrouptomakea

prediction.

参考试卷答案

、写出以下单词的中文意思（每小题0.5分，共10分）

1accuracyn.精确（性），准确（性）IIcustomizevt.定制，定做；用户化

2actuatorn.执行器12definitionn.定义

3adjustV.调整，调节；适应；校准13defuzzificationn.逆模糊化，去模糊化

4agentn.实体；代理14deploymentn.部署

5algorithmn.算法15effectorn.效应器

6analogyn.类推16entityn.实体

7attributen.属性；性质；特征17extractV.提取，提炼

8backtrackvi.回溯18feedbackn反馈

9blockchainn.区块链19finiteadj.有限的；限定的

1020n.构架；框架；（体系的）

clusterv.聚集n.团，群，簇framework

结构

二、根据给出的中文意思，写出英文单词（每小题0.5分，共10分）

1V.收集，搜集gather11n.神经元；神经细胞neuron

2adj.嵌入的，内置的inbuilt12n.节点node

3n.指示器；指标indicator13V.运转；操作operate

4n.基础设施，基础架构infrastructure14n.模式pattern

5v.合并：集成integrate15V.察觉，发觉perceive

6n.解释器，解释程序interpreter16n.前提premise

7n.迭代；循环iteration17adj.程序的；过程的procedural

8n.库library18n.回归regression

919adj.健壮的，强健的；

n.元数据metadatarobust

结实的

10V.监视；控制；监测monitor20V.筛选screen

三、根据给出的短语，写出中文意思（每小题1分，共10分）

1dataobject数据对象

2cybersecurity网络安全

3smartmanufacturing智能制造

4clusteredsystem集群系统

5datavisualization数据可视化

6opensource开源

7analyzetext分析文本

8cloudcomputing云计算

9computationpower计算能力

10objectrecognition物体识别

四、根据给出的中文意思，写出英文短语（每小题1分，共10分）

1数据结构datastructure

2决策树decisiontree

3演绎推理deductivereasoning

4贪婪最佳优先搜索greedybest-firstsearch

5隐藏模式，隐含模式hiddenpattern

6知识挖掘knowledgemining

7逻辑推理logicalreasoning

8预测性维护predictivemaintenance

9搜索引擎searchengine

10文本挖掘技术textminingtechnique

五、写出以下缩略语的完整形式和中文意思（每小题1分，共10分）

缩略语完整形式中文意思

1ANNArtificialNeuralNetwork人工神经网络

2ARAugmentedReality增强现实

3BFSBreadth-FirstSearch宽度优先搜索

4CVComputerVision计算机视觉

5DFSDepth-FirstSearch深度优先搜索

6ESExpertSystem专家系统

7IAIntelligentAgent智能体

8KNNK-NearestNeighborK最近邻算法

9NLPNaturalLanguageProcessing自然语言处理

10VRVirtualReality虚拟现实

六、阅读短文，回答问题（每小题2分，共10分）

I.Anartificialneuralnetwork(ANN)isthepieceofacomputingsystemdesignedtosimulatethe

waythehumanbrainanalyzesandprocessesinformation.Itisthefoundationofartificial

intelligence(AI)andsolvesproblemsthatwouldproveimpossibleordifficultbyhumanor

statisticalstandards.

2.Eachneuronismadeupofacellbodythatisresponsibleforprocessinginformationbycarrying

informationtowards(inputs)andaway(outputs)fromthebrain.

3.The