管理信息系统 MIS课件：ch09 Complex Decisions and Artificial Intelligence

1、Introduction to MIS1Copyright 1998-2002 by Jerry PostIntroduction to MISChapter 9Complex Decisions and Artificial IntelligenceIntroduction to MIS2The labvSummaryACCESS, ER, IDEF0, IDEF3, DFD, ROSE, HCIThe projectsvTwo groups demo (Project List)Home workvUsing Access to realize a “customer self bank

2、loan querying system”, which can:1.Allow customer to input data from the website of the system2.After answering querying, show the loan decision3.Maintain all customer informationIntroduction to MIS3Computer analysisof data and model.DecisionOperationsTacticsStrategyNeural networkCompanyComplex Deci

3、sions& Artificial IntelligenceIntroduction to MIS4OutlineSpecialized ProblemsExpert SystemvDefinitionvBuilding Expert SystemsvDSS and ESKnowledge ManagementAIMore Specialized ProblemsDSS, ES, and AIE-Business and Software AgentsConclusionCases: FranchisesAppendix: E-mail RulesIntroduction to MIS

4、5Requirement for Decision Making:Specialized ProblemsDiagnosticsSpeedConsistencyTrainingCase-based reasoningIntroduction to MIS6Expert SystemKnowledge BaseSymbolic & Numeric KnowledgeIf income 20,000or expenses 3000and good credit historyor . . .Then 10% chance of defaultRulesExpert decisionsmad

5、e bynon-expertsExpertHow to manage rules?The decision tree?Introduction to MIS7Expert System ExampleCamcorder selection by ExSysLink: http:/ ItMore: Pallas food:Map: http:/ accordAirplaneIntroduction to MIS8ES Example: bank loanWelcome to the Loan Evaluation System.What is the purpose of the loan? c

6、arHow much money will be loaned? 10,000For how many years? 5The current interest rate is 10%.The payment will be $212.47 per month.What is the annual income? 24,000What is the total monthly payments of other loans? Why?Because the payment is more than 10% of the monthly income.What is the total mont

7、hly payments of other loans? 50.00The loan should be approved, there is only a 2% chance of default.Forward ChainingIntroduction to MIS9Payments 10%monthly income?Other loanstotal k cluster-size) do (for (j 0 (+ 1 j ) exit when (= j k) do (connect unit cluster k output o -A to unit cluster j input i

8、 - A ) . . . )Maintained by expert system shellProgrammerCustom program in LISPES DevelopmentES ShellsvGuruvExsysCustom ProgrammingvLISPvPROLOGIntroduction to MIS14Some Expert System ShellsCLIPSvOriginally developed at NASAvWritten in CvAvailable free or at low costvhttp:/ in JavavGood for Web appli

9、cationsvAvailable free or at low costv/jess/ExSysvCommercial system with many Introduction to MIS15DSS and ESDSSESgoalhelp user make decisionprovide expert advicemethoddata - model - presentationasks questions,applies rules, explainstype ofproblemsgeneral, limited by user

10、modelsnarrow domainIntroduction to MIS16ES Problem SuitabilityNarrow, well-defined domainSolutions require an expertComplex logical processingHandle missing, ill-structured dataNeed a cooperative expertRepeatable decisionIntroduction to MIS17Limitations of ESFragile systemsvSmall environmental. chan

11、ges can force revision. of all of the rules.MistakesvWho is responsible?Expert?Multiple experts?Knowledge engineer?Company that uses it?Vague rulesvRules can be hard to define.Conflicting expertsvWith multiple opinions, who is right?vCan diverse methods be combined?Unforeseen eventsvEvents outside o

12、f domain can lead to nonsense decisions.vHuman experts adapt.vWill human novice recognize a nonsense result?Introduction to MIS18Knowledge ManagementA collection of a documents and datavCreated by expertsvSearchablevWith links to related topicsvHighly organized groupwareEmphasizing contextMain probl

13、emconvincing everyone to enter and update the documentsExampleNew: ontology and semanticsIntroduction to MIS19Example of Knowledge ManagementExamplebusiness decisionsvStore problem, all notes, decision factors, commentsvFuture problems, managers can search the database and find similar problemsvBett

14、er and more efficient decisions if you know the original problems, discussions, and contingency plansFMEA (Failure Model Effect Analysis)Problem descriptiontitlefrequencyprioritydifficultysolutionstatusrelativesnote12ROI?=Introduction to MIS20AI Research AreasComputer SciencevParallel ProcessingvSym

15、bolic ProcessingvNeural NetworksRobotics ApplicationsvVisual PerceptionvTactilityvDexterityvLocomotion & NavigationNatural LanguagevSpeech RecognitionvLanguage TranslationvLanguage ComprehensionCognitive SciencevExpert SystemsvLearning SystemsvKnowledge-Based SystemsIntroduction to MIS21More Spe

16、cilised ProblemsPattern RecognitionMachine VisionVoice and Speech RecognitionLanguage ComprehensionRobotics and MotionStatistics, Uncertainty, and Fuzzy LogicIntroduction to MIS22Output CellsSensory Input CellsHidden LayerSome of the connections3-274Input weightsIncompletepattern/missing inputs.Neur

17、al Network: Pattern recognitionIntroduction to MIS23Machine Vision ExampleThe Department of Defense has funded Carnegie Mellon University to develop software that is used to automatically drive vehicles. One system (Ranger) is used in an army ambulance that can drive itself over rough terrain for up

18、 to 16 km. ALVINN is a separate road-following system that has driven vehicles at speeds over 110 kph for as far as 140 km.DASO的项目三荾的项目Introduction to MIS24Speech RecognitionLook at the users voice command:Copy the red, file the blue, delete the yellow mark.Now, change the commas slightly.Copy the r

19、ed file, the blue delete, the yellow mark.I saw the Grand Canyon flying to New York.EmergencyVehiclesNoParkingAny TimeIntroduction to MIS25Subjective Definitionstemperaturereference pointe.g., averagetemperaturecoldhotMoving farther from the reference pointincreases the chance that the temperature i

20、sconsidered to be different (cold or hot).Subjective (fuzzy) DefinitionsIntroduction to MIS26DSS, ES, and AI: Bank ExampleDecision Support SystemExpert SystemArtificial IntelligenceName Loan#Late AmountBrown 25,000 51,250Jones 62,000 1 135Smith 83,000 32,435.DataIncomeExisting loansCredit reportMode

21、lLend in all but worst casesMonitor for late and missing payments.OutputES RulesWhat is the monthly income?3,000What are the total monthly payments on other loans? 450How long have they had the current job? 5 years. . .Should grant the loan since there is only a 5% chance of default.Determine Rulesl

22、oan 1 data: paidloan 2 data: 5 lateloan 3 data: lostloan 4 data: 1 lateData/Training CasesNeural Network WeightsEvaluate new data,make recommendation.Loan OfficerIntroduction to MIS27Decision Support SystemExpert SystemArtificial IntelligenceDataa estimate salesK order setup costh estimate holding c

23、ostModelQ* = sqrt ( 2ak / h )OutputtimeQ*Inventory Levelsreorder pointsChoosing an Inventory SystemWhat is the cost of running out of inventory? 45,000 per dayWhat are daily profits? 250,000How many suppliers are there? 8Can more suppliers be added in an emergency? noHow close is the nearest supplie

24、r? 10 kilometresHow reliable is this supplier? very. . .Best choice is to use Just-In-Time inventory system. Only a 2% chance of running out of inventory for more than 2 days. . . .Automatically Analyzesite 1 data: JITsite 2 data: EOQsite 3 data: JITsite 4 data: hybridData/Training CasesNeural Netwo

25、rk WeightsEvaluate new data,make recommendation.DSS, ES and AI: Inventory ExampleIntroduction to MIS28Vacation ResortsSoftware agentResort DatabasesLocate &book trip.Software AgentsO-O based, an objectIndependentNetworks/CommunicationUsesvSearchvNegotiatevMonitorSOAIntroduction to MIS29Conclusio

26、n and AI QuestionsDSS, ES, KM, AI, the definition and features High level of Computers ApplicationsWhat is intelligence?vCreativity?vLearning?vMemory?vAbility to handle unexpected events?vMore?Can machines ever think like humans?How do humans think?Do we really want them to think like us?Introductio

27、n to MIS30FeaturesDSSESKMAIGoalhelpMake decisionMethodDataRulesRules & DocumentsCasesProblemgeneralnarrowSpecial areaSpecial areaQuestion: within a general ERP system, is there any potential for these decision and analysis?Introduction to MIS31Cases: FranchisesIntroduction to MIS32Cases: Mrs. Fi

28、eldsBlockbuster VideoWhat is the companys current status?What is the Internet strategy?How does the company use information technology?What are the prospects for the industry?Introduction to MIS33Appendix: E-Mail Rules - FoldersFolders make it easy to organize and handle your mail.Simple rules from

29、the Tools + Organize button move messages directly to the specified folder.Introduction to MIS34Rules: ConditionsThe Tools + Rules Wizard makes it easy to create rules. Begin with a blank rule.Set the ConditionsSet the ActionsDefine ExceptionsA sample rule to handle unsolicited credit card applicati

30、ons.Introduction to MIS35Rules: ActionsChoose an action.You can choose multiple actions, but be careful. The marking options are often combined.Introduction to MIS36Rules: ExceptionsRules can have exceptions. For example, you might want to delete company newslettersunless one has your name in it.Int

31、roduction to MIS37Rule Sequences: Decision TreeFrom boss, Subject: ExpensesMessage from ExpenseAccountingExpenses FolderSet expenses categoryMove itRule 1Rule 2Expenses categorySubject: PaymentRule 3Action: Mark important and notify.决策运作层战术层战略层神经网络公司公司知识库符号及数字信息如果如果 income 20,000或者 expenses 收入的 5% 计算其它贷款支付的总额 计算月收入的支付百分率 如果该百分率 25%如果新的贷款 10%，则发放贷款否则 如果月花费总额 收入的 40%，则发放贷款 否则 如果 50%，而且是5年以上的客户， 或者 60%，而且是10年以上的客户，而且在同一居所居住了5年以上，则发放贷款支付是否 月收入的10%?其它贷款总额是否 月收入的 10% 其