離散事件系統(tǒng)仿真：英文版

定　價：￥65.00

作　者：	（美）Jerry Banks等著
出版社：	機械工業(yè)出版社
叢編項：	經(jīng)典原版書庫
標　簽：	系統(tǒng)仿真/虛擬現(xiàn)實

購買這本書可以去

ISBN：	9787111171942	出版時間：	2005-09-01	包裝：	膠版紙
開本：	24cm	頁數(shù)：	608	字數(shù)：

內(nèi)容簡介

　　內(nèi)容簡介目錄　本書論述了離散事件系統(tǒng)仿真的所有重要方面，全面討論了正確的數(shù)據(jù)收集與分析、解析技術(shù)的使用、模型的驗證以及適當?shù)姆抡鎸嶒炘O(shè)計。熟悉微積分、概率論以及初等統(tǒng)計學的知識將有助于閱讀本書。第4版中對全書內(nèi)容進行了廣泛的更新，反映了軟件與方法學的最新進展，并對某些章節(jié)進行了徹底修訂，同時增加了有關(guān)制造與物料儲運系統(tǒng)仿真、計算機系統(tǒng)仿真以及通信系統(tǒng)仿真的新章節(jié)。本書可作為高等院校工程系、管理系、計算機科學系等高年級本科生或低年級研究生的仿真課程的教材。讀者可以從網(wǎng)站www.bcnn.net中獲取本書的相關(guān)資料。目錄： 1： Introduction 2： Simulation Examples 3： General Principles 4： Simulation Software 5： Statistical Models in Simulation 6： Queueing Models 7： Random-number Generation 8： Random-variate Generation 9： Input Modeling 10： V&V 11： Output Analysis for a Single Model 12： Comparing Multiple Designs 13： Simulation of Mfg. & MH Systems 14： Simulation of Computer Systems 15： Simulation of Communication Systems

作者簡介

　　JerryBanks佐治亞理工大學工業(yè)及系統(tǒng)工程學院退休教授。目前他是一名高級仿真技術(shù)咨詢專家。他寫了很多著作，是包括工業(yè)工程師協(xié)會（IIE）在內(nèi)的許多技術(shù)學會的全職會員，并在2002年成為IIE的特別會員。BrooksAutomation公司AutoMod產(chǎn)品部咨詢技術(shù)經(jīng)理。他是一名獨立的仿真咨詢專家，并在佐治亞理工大學、佛羅里達大學以及威斯康星大學麥迪遜分校任教。BarryL.Nelson西北大學工業(yè)工程及管理科學系教授、工程管理計劃的碩士研究生導師，并擔任TIMS仿真學會的主席。他的研究方向為隨機系統(tǒng)模型的計算機仿真實驗的設(shè)計和分析。他已經(jīng)發(fā)表了大量文章，并出版了兩本專著。DavidM.Nicol伊利諾伊大學厄巴納-尚佩恩分校電氣及計算機工程系教授。他在并行及分布式離散事件系統(tǒng)仿真領(lǐng)域有著豐富的經(jīng)驗。他目前的研究方向是超大系統(tǒng)特別是通信及其他基礎(chǔ)設(shè)施的建模與仿真。Nicol教授同時也是IEEE的特別會員。相關(guān)圖書80X86匯編語言與計算機體系結(jié)構(gòu)計算機科學概論（英文版·第2版）分布式系統(tǒng)概念設(shè)計Java2專家導引（英文版·第3版）復分析基礎(chǔ)及工程應用（英文版.第3版）支持向量機導論（英文版）Java程序設(shè)計導論（英文版·第5版）數(shù)據(jù)挖掘：實用機器學習技術(shù)（英文版·第2版）UML參考手冊（第2版）數(shù)字通信導論復雜SoC設(shè)計（英文版）UML參考手冊（英文版·第2版）計算理論導引實用軟件工程（英文版）計算機取證（英文版）EffectiveC#（英文版）UNIX教程（英文版·第2版）軟件測試（英文版第2版）設(shè)計模式精解（英文版第2版）實分析和概率論-經(jīng)典原版書庫（英文版.第2版）軟件過程改進（英文版）計算機體系結(jié)構(gòu)：量化研究方法：第3版調(diào)和分析導論（英文第三版）人工智能：智能系統(tǒng)指南（英文版）第二版電力系統(tǒng)分析（英文版·第2版）面向計算機科學的數(shù)理邏輯：系統(tǒng)建模與推理（英文版·第2版）數(shù)學規(guī)劃導論英文版抽樣理論與方法（英文版）機器視覺教程（英文版）（含盤）電子設(shè)計自動化基礎(chǔ)（英文版）Java教程（英文版·第2版）軟件需求管理：用例方法（英文版·第2版）基于FPGA的系統(tǒng)設(shè)計（英文版）基于用例的面向方面軟件開發(fā)（英文版）Linux內(nèi)核編程必讀-經(jīng)典原版書庫

圖書目錄

Preface
AbouttheAuthors
IIntroductiontoDiscrete-EventSystemSimulation
Chapter1IntroductiontoSimulation
1.1WhenSimulationIstheAppropriateTool
1.2WhenSimulationIsNotAppropriate
1.3AdvantagesandDisadvantagesofSimulation
1.4AreasofApplication
1.5SystemsandSystemEnvironment
1.6ComponentsofaSystem
1.7DiscreteandContinuousSystems
1.8ModelofaSystem
1.9TypesofModels
1.10Discrete-EventSystemSimulation
1.11StepsinaSimulationStudy
References
Exercises
Chapter2SimulationExamples
2.1SimulationofQueueingSystems
2.2SimulationofInventorySystems
2.3OtherExamplesofSimulation
2.4Summary
References
Exercises
Chapter3GeneralPrinciples
3.1ConceptsinDiscrete-EventSimulation
3.1.1TheEventScheduling/TimeAdvanceAlgol
3.1.2WorldViews
3.1.3ManualSimulationUsingEventSchedulin~
3.2ListProcessing
3.2.1Lists:BasicPropertiesandOperations
3.2.2UsingArraysforListProcessing
3.2.3UsingDynamicAllocationandLinkedList:
3.2.4AdvancedTechniques
3.3Summary
References
Exercises
Chapter4SimulationSoftware
4.1HistoryofSimulationSoftware
4.1.1ThePeriodofSearch(1955-60)
4.1.2TheAdvent(1961-65)
4.1.3TheFormativePeriod(1966-70)
4.1.4TheExpansionPeriod(1971-78)
4.1.5ConsolidationandRegeneration(1979-86)
4.1.6IntegratedEnvironments(1987-Present)
4.2SelectionofSimulationSoftware
4.3AnExampleSimulation
4.4SimulationinJava
4.5SimulationinGPSS
4.6SimulationinSSF
4.7SimulationSoftware
4.7.1Arena
4.7.2AutoMod
4.7.3Extend
4.7.4Flexsim
4.7.5MicroSaint
4.7.6ProModel
4.7.7QUEST
4.7.8SIMUL8
4.7.9WITNESS
&8ExperimentationandStatistical-AnalysisTools
4.8.1CommonFeatures
4.8.2Products
References
Exercises
IIMathematicalandStatisticalModels
Chapter5StatisticalModelsinSimulation
5.1ReviewofTerminologyandConcepts
5.2UsefulStatisticalModels
5.3DiscreteDistributions
5.4ContinuousDistributions
5.5PoissonProcess
5.5.1PropertiesofaPoissonProcess
5.5.2NonstationaryPoissonProcess
5.6EmpiricalDistributions
5.7Summary
References
Exercises
Chapter6QueueingModels
6.1CharacteristicsofQueueingSystems
6.1.1TheCallingPopulation
6.1.2SystemCapacity
6.1.3TheArrivalProcess
6.1.4QueueBehaviorandQueueDiscipline
6.1.5ServiceTimesandtheServiceMechanism
6.2QueueingNotation
6.3Long-RunMeasuresofPerformanceofQueueingSystems
6.3.1Time-AverageNumberinSystemL
6.3.2AverageTimeSpentinSystemPerCustomerw
6.3.3TheConservationEquation:L=λw
6.3.4ServerUtilization
6.3.5CostsinQueueingProblems
6.4Steady-StateBehaviorofInfinite-PopulationMarkovianModels
6.4.1Single-ServerQueueswithPoissonArrivalsandUnlimitedCapacity:M/G/1
6.4.2MultiserverQueue:M/M/c/∞/∞
6.4.3MultiserverQueueswithPoissonArrivalsandLimitedCapacity:M/M/c/N/oo
6.5Steady-StateBehaviorofFinite-PopulationModels(M/M/c/K/K)
NetworksofQueues
Summary
References
Exercises
IIIRandomNumbers
Chapter7Random-NumberGeneration
7.1PropertiesofRandomNumbers
7.2GenerationofPseudo-RandomNumbers
7.3TechniquesforGeneratingRandomNumbers
7.3.1LinearCongmentialMethod
7.3.2CombinedLinearCongruentialGenerators
7.3.3Random-NumberStreams
7.4TestsforRandomNumbers
7.4.1FrequencyTests
7.4.2TestsforAutocorrelation
7.5Summary
References
Exercises
Chapter8Random-VariateGeneration
8.1Inverse-TransformTechnique
8.1.1ExponentialDistribution
8.1.2UniformDistribution
8.1.3WeibullDistribution
8.1.4TriangularDistribution
8.1.5EmpiricalContinuousDistributions
8.1.6ContinuousDistributionswithoutaClosed-FormInverse
8.1.7DiscreteDistributions
8.2Acceptance-RejectionTechnique
8.2.1PoissonDistribution
8.2.2NonstationaryPoissonProcess
8.2.3GammaDistribution
8.3SpecialProperties
8.3.1DirectTransformationfortheNormalandLognormalDistributions
8.3.2ConvolutionMethod
8.3.3MoreSpecialProperties
8.4Summary
References
Exercises
AnalysisofSimulationData
Chapter9InputModeling
9.1DataCollection
9.2IdentifyingtheDistributionwithData
9.2.1Histograms
9.2.2SelectingtheFamilyofDistributions
9.2.3Quantile-QuantilePlots
9.3ParameterEstimation
9.3.1PreliminaryStatistics:SampleMeanandSampleVariance
9.3.2SuggestedEstimators
9.4Goodness-of-FitTests
9.4.1Chi-SquareTest
9.4.2Chi-SquareTestwithEqualProbabilities
9.4.3Kolmogorov-SmimovGoodness-of-FitTest
9.4.4p-Valuesand"BestFits"
9.5FittingaNonstationaryPoissonProcess
9.6SelectingInputModelswithoutData
9.7MultivariateandTime-SeriesInputModels
9.7.1CovarianceandCorrelation
9.7.2MultivariateInputModels
9.7.3Time-SeriesInputModels
9.7.4TheNormal-to-AnythingTransformation
9.8Summary
References
Exercises
Chapter10VerificationandValidationofSimulationModels
10.1Model-Building,Verification,andValidation
10.2VerificationofSimulationModels
10.3CalibrationandValidationofModels
10.3.1FaceValidity
10.3.2ValidationofModelAssumptions
10.3.3ValidatingInput-OutputTransformations
10.3.4Input-OutputValidation:UsingHistoricalInputData
10.3.5Input-OutputValidation:UsingaTuringTest
10.4Summary
References
Exercises
Chapter11OutputAnalysisforaSingleModel
11.1TypesofSimulationswithRespecttoOutputAnalysis
11.2StochasticNatureofOutputData
11.3MeasuresofPerformanceandTheirEstimation
H.3.1PointEstimation
11.3.2Confidence-IntervalEstimation
11.4OutputAnalysisforTerminatingSimulations
11.4.1StatisticalBackground
11.4.2ConfidenceIntervalswithSpecifiedPrecision
11.4.3Quantiles
11.4.4EstimatingProbabilitiesandQuantilesfromSummaryData
11.5OutputAnalysisforSteady-StateSimulations
11.5.1InitializationBiasinSteady-StateSimulations
11.5.2ErrorEstimationforSteady-StateSimulation
l1.5.3ReplicationMethodforSteady-StateSimulations
11.5.4SampleSizeinSteady-StateSimulations
11.5.5BatchMeansforIntervalEstimationinSteady-StateSimulations
11.5.6Quantiles
11.6Summary
References
Exercises
Chapter12ComparisonandEvaluationofAlternativeSystemDesigns
12.1ComparisonofTwoSystemDesigns
12.1.1IndependentSamplingwithEqualVariances
12.1.2IndependentSamplingwithUnequalVariances
12.1.3CommonRandomNumbers(CRN)
12.1.4ConfidenceIntervalswithSpecifiedPrecision
12.2ComparisonofSeveralSystemDesigns
12.2.1BonferroniApproachtoMultipleComparisons
12.2.2BonferroniApproachtoSelectingtheBest
12.2.3BonferroniApproachtoScreening
12.3Metamodeling
12.3.1SimpleLinearRegression
12.3.2TestingforSignificanceofRegression
12.3.3MultipleLinearRegression
12.3.4Random-NumberAssignmentforRegression
12.4OptimizationviaSimulation
12.4.1WhatDoes'OptimizationviaSimulation'Mean?
12.4.2WhyisOptimizationviaSimulationDifficult?
12.4.3UsingRobustHeuristics
12.4.4AnIllustration:RandomSearch
Summary
References
Exercises
VApplications
Chapter13SimulationofManufacturingandMaterial-HandlingSystems
13.1ManufacturingandMaterial-HandlingSimulations
13.1.1ModelsofManufacturingSystems
13.1.2ModelsofMaterial-Handling
13.1.3SomeCommonMaterial-HandlingEquipment
13.2GoalsandPerformanceMeasures
13.3IssuesinManufacturingandMaterial-HandlingSimulations
13.3.1ModelingDowntimesandFailures
13.3.2Trace-DrivenModels
13.4CaseStudiesoftheSimulationofManufacturingandMaterial-HandlingSystems
13.5ManufacturingExample:AJob-ShopSimulation
13.5.1SystemDescriptionandModelAssumptions
13.5.2PresimulationAnalysis
13.5.3SimulationModelandAnalysisoftheDesignedSystem
13.5.4AnalysisofStationUtilization
13.5.5AnalysisofPotentialSystemImprovements
13.5.6ConcludingWords
13.6Summary
References
Exercises
Chapter14SimulationofComputerSystems
14.1Introduction
14.2SimulationTools
14.2.1ProcessOrientation
14.2.2EventOrientation
14.3ModelInput
14.3.1ModulatedPoissonProcess
14.3.2Virtual-MemoryReferencing
14.4High-LevelComputer-SystemSimulation
14.5CPUSimulation
14.6MemorySimulation
14.7Summary
References
Exercises
Chapter15SimulationofComputerNetworks
15.1Introduction
15.2TrafficModeling
15.3MediaAccessControl
15.3.1Token-PassingProtocols
15.3.2Ethernet
15.4DataLinkLayer
15.5TCP
15.6ModelConstruction
15.6.1Construction
15.6.2Example
15.7Summary
References
Exercises
Appendix
Index