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1、Syllabus ofForecasting and Decision-making Theory andMethodsCourse Code：Total Credit Hours： 48Experiment Hours： 0Practice Hours： 0Course Name： Forecasting and decision-making theory and methodsCredits： 3Lecture Hours： 48Programming Hours： 0Total Number of Experimental (Programming) Projects 0Where,
2、Compulsory ( 0 ), Optional ( 0 ).School ： School of BusinessTarget Major： Industrial EngineeringI、Course Nature & AimsCourse Nature: Forecasting and decision-making theory and methods is a main course of management science and an important elective course for related majors. It is an important basic
3、 course that allows students to systematically master the concepts, knowledge, theories and basic techniques of predictive decision-making. Use the forecasting and decision-making methods and technical analysis to solve practical problems and to cultivate students1 thinking and ability in scientific
4、 prediction and decision-making.Course purpose: Through the study of this course, students can understand the concept, function and meaning of forecasting, systematically master commonly used forecasting methods and technologies, and be able to apply the forecasting methods learned in conjunction wi
5、th actual problems to perform forecasting analysis to provide support for scientific decision making Students understand the concepts, procedures and basic steps of decision-making, systematically master common decision-making methods, and can apply the learned decision-making methods to make decisi
6、on analysis. In view of the characteristics of the forecasting and decision-making course, pay attention to the cultivation of students scientific decision-making thinking in the teaching process, emphasizing the combination of theoretical learning and applied practice, focusing on the combination o
7、f qualitative analysis and quantitative analysis, for students* subsequent learning, practice and future work Lay a good foundation for development.II Course Objectives1. Moral Education and Character Cultivation.Learn the theory, methods and techniques of forecasting and decision-making through the
8、 course to have a comprehensive understanding of the knowledge related to forecasting and decision-making. By explaining the11、 12)extrapolation forecasting methods, Markov forecasting method applications, gray Sequence operator, grey prediction model, grey prediction technologyObjective 2(indices 1
9、、2、3、4、5、6、7、8、9、1()、11、12)Breakeven analysis, multi-scheme decision analysis, risk-based decision analysis methods, analytic hierarchy process, data envelopment analysis method, uncertain decision criteria, basic concepts of gray decision, gray target decision model, gray cluster decision model5101
10、02550Total15202045100YUI、Course ResourcesTextbooks：Liu Sifeng, Jian Lirong, Mi Chuanmin. Management Forecast and Decision Method (Third Edition) M.Beijing: Science Press, 2018.Bibliography：1 . Liu Sifeng. Forecasting Methods and Technology M. Beijing: Higher Education Press, 2009.2 .Xu Guoxiang. Sta
11、tistical Forecasting and Decision Making (Fourth Edition) M. Shanghai: ShanghaiUniversity of Finance and Economics Press, 2012.IX、NotesPrerequisites:Follow-up Courses: NoContents and Requirements of Students Self-study: NoBilingual Teaching or Not: NoRequirements and Proportion of Bilingual Teaching
12、: NoDiscipline and Considerations of Practice Session: no practice sessionNotes: NoAuthor：Approved by：development history of forecasting and decision-making theory and the process of establishing relevant theories and technologies, understand how predecessors think in the development process of fore
13、casting and decision-making, how to overcome the obstacles encountered, and help students establish scientific thinking methods and courage to face challenges. From the perspective of applying forecasting and decision-making theory to promote innovation-driven development in China, taking the resear
14、ch work of outstanding contributors as the carrier, integrating the socialist core values education into the curriculum teaching content and all aspects of the entire teaching process, highlighting value guidance, knowledge transfer and ability training. To help students correctly understand the law
15、s of history, accurately grasp the basic national conditions, grasp the scientific world outlook and methodology, and promote the establishment of a correct world outlook and values.2 .Course ObjectivesThrough the study of this course, students1 qualities, skills, knowledge and abilities obtained ar
16、e as follows：Objective 1. Master the relevant concepts of forecasting concepts, basic principles, common methods, and evaluation of forecasting effects, and be able to apply forecasting methods learned to forecast and analyze actual problems. (Corresponding to Chapter 1-7, supporting for graduation
17、requirements index 1 2、3、4、5、9、10 11、 12)Objective 2. Systematically master the concept of decision-making, basic theory and typical methods, and can apply the learned decision-making methods to analyze and make decisions on actual problems.(Corresponding to Chapter 8-13, supporting for graduation r
18、equirements index 1 2、3、4 5、6、7、8、9、 10、Ik 12). Supporting for Graduation RequirementsThe graduation requirements supported by course objectives are mainly reflected in the graduation requirements indices 1 -12 , as follows:Supporting for Graduation RequirementsIH Basic Course ContentCourseObjective
19、sGraduationRequirementsIndices and Contents Supporting for Graduation RequirementsTeachingTopicsLevel ofSupportIndicesContentsObjective1Master solid mathematical basic theory and good computer skillsIndex 2,3,52)Ability to apply mathematics, science and engineering knowledge3) Ability to understand
20、and use the latest industrial engineering techniques and tools5) Ability to analyze and interpret dataChapter2、 3、 4、5、 6、 7、9、10、11、 12、13MObjective2Master basic knowledge and skills in economic management, humanities andIndex7,8,9,10,11,127) Professional and ethical responsibilities8) Ability to c
21、ommunicate effectively9) Lifelong learning cognition and ability10) Understanding of contemporary issues11) Ability to understand the impact ofChapter1、 2、 3、4、 5、 6、7、 8、 9、1()、11、Msocial sciencesengineering solutions on the global, economic, environmental and social aspects with broad knowledge12)
22、 A high humanistic quality12、13Objective3Master comprehensive professional ability to analyze, plan, design, manage and operate complex socio-economic activity systemsIndex2,3,4,5,6,112)Ability to apply mathematics, science and engineering knowledge3) Ability to understand and use the latest industr
23、ial engineering techniques and tools4) System planning and design capabilities5) Ability to analyze and interpret data6) Teamwork and leadership skills11) Ability to understand the impact of engineering solutions on the global, economic, environmental and social aspects with broad knowledgeChapter2、
24、 3、 4、5、 6、 7、9、10、11、 12、13HOverview of Forecasting (supporting course objectives * 1 *)1.1 IntroductionThe role of prediction1.2 Basic principles of forecastingClassification of predictions1.3 Forecasting proceduresPrediction accuracy and valueTeaching Requirements: Through the study in Chapter 1,
25、 students are required to clarify the concept of forecasting; understand the role and significance of forecasting; master the basic principles of forecasting and the classification of forecasting; be familiar with forecasting procedures and applications; and correctly understand the value of forecas
26、ting.Key Points： Prediction concept and function; prediction classification, prediction program and application; prediction accuracy and value.Difficult Points：Chapter 1 Qualitative Forecasting Method (supporting course objectives * 1*)Introduction2.1 Market survey forecast methodExpert prediction2.
27、2 Subjective probability methodOmen prediction methodTeaching Requirements: Through the study in Chapter 2, students are required to master the market survey forecasting method, expert forecasting method, and subjective probability forecasting method; they can correctly use the learned methods to ma
28、ke predictions.Key Points： market research and forecasting method; brainstorming method; Delphi method; subjective probability forecasting methodDifficult Points：Chapter 2 Time Series Smooth Prediction Method (supporting course objectives * 1 *)Overview of time series3.1 Moving average methodExponen
29、tial smoothing3.2 Difference exponential smoothingAdaptive filtering methodTeaching Requirements: Through the study in Chapter 3, students are required to understand the concept and combination of time series, master the time series smooth prediction method, moving average prediction method, differe
30、ntial exponential smooth prediction method, and adaptive filtering method; be able to use various skills proficiently The time series smooth prediction method predicts actual problems.Key Points： the concept of time series and its combination; moving average prediction method; exponential smoothing
31、prediction method; adaptive filtering methodDifficult Points：Chapter 3 Regression Analysis and Forecasting Method (supporting course objectives * 1 *)Introduction4.1 Unary linear regression prediction methodMultiple linear regression prediction method4.2 Dummy variable regression predictionNonlinear
32、 regression prediction methodTeaching Requirements:Through the study in Chapter 4, students are required to understand the concepts and assumptions of univariate linear regression models and multiple linear regression models, master the estimation and testing methods of linear regression model param
33、eters, and be able to use linear regression models to solve practical problems ; Understand the regression model with dummy variables, and be able to select explanatory variables; Understand the different forms and classifications of nonlinear regression models.Key Points： linear regression predicti
34、on methods, regression models with dummy variables, nonlinear regression prediction modelsDifficult Points：Chapter 4 Trend Extrapolation Forecasting Method (supporting course objectives * 1*)Exponential curve method5.1 Modified exponential curve method5.2 Growth curve method5.3 Envelope curve method
35、Teaching Requirements: Through the study in Chapter 5, students are required to master the exponential curve method and the growth curve method; understand the envelope curve prediction method.Key Points： exponential curve method and modified exponential curve method; growth curve method; envelope c
36、urve methodDifficult Points：Chapter 5 Markov Forecasting Method (supporting course objectives * 1 *)Introduction to Markov Chain6.1 Forecast of commodity sales statusMarket Share Forecast6.2 Expected profit forecastTeaching Requirements: Through the study in Chapter 6, students are required to maste
37、r the concept of Markov chain and the estimation method of state transition probability. They can use the Markov chain and its state transition probability to predict the sales status, market share and expected profit of the commodity .Key Points： Markov chain; commodity sales status prediction; mar
38、ket share forecast; expected profit forecastDifficult Points：Chapter 6 Grey System Forecasting (supporting course objectives * 1 *)Introduction7.1 Sequence operator and gray information miningGrey system prediction model7.2 Grey system prediction technologyTeaching Requirements: Through the study in
39、 Chapter 7, students are required to understand the nature of the buffer operator km and buffer operator, to master the structure and function of the weakened buffer operator, the enhanced buffer operator, the accumulation operator, and the accumulation operator; (1,1) The basic form of the model an
40、d its scope of use; master the interval prediction and gray catastrophe prediction methods, and understand the waveform prediction methods.Key Points： sequence operators and gray information mining; gray prediction model; gray prediction technologyDifficult Points：Chapter 7 Overview of Decision-maki
41、ng (supporting course objectives * 2*)Connotation and basic elements of decision analysis8.1 Classification and basic principles of decision analysis8.2 Basic steps of decision analysisOverview of decision analysis methodsTeaching Requirements: Through the study in Chapter 8, students are required t
42、o be familiar with the concept, development status and basic elements of decision analysis; master the classification, basic principles and basic steps of decision analysis.Key Points： decision analysis concepts and basic elements; decision analysis classification, procedures and basic principles; d
43、ecision analysis stepsDifficult Points：Chapter 8 Definite Decision Analysis (supporting course objectives * 2*)Overview of Definitive Decision Analysis9.1 Profit and loss decision analysisMulti-scheme investment decisionTeaching Requirements:Through the study in Chapter 9, students are required to b
44、e familiar with the process and steps of definite decision-making; master the basic theoretical methods of profit and loss decision-making analysis; master the static and dynamic evaluation methods of independent investment program decisions; The main evaluation method.Key Points： deterministic deci
45、sion analysis method, profit and loss decision analysis method, multi-project investment decision methodDifficult Points：Chapter 9 Risk-Based Decision Analysis (supporting course objectives * 2*)Expectation criteria for risk-based decision-making and its application10.1 Decision tree analysis method
46、Bayesian Decision Method10.2 Utility decision methodTeaching Requirements: Through the study in Chapter 10, students are required to be familiar with the connotation and basic ideas of risk-based decision-making; master the expected value criterion decision-making method; familiar with the basic pri
47、nciples and procedures of decision tree analysis method; master the basic theoretical method of Bayesian decision-making; familiar The basic method of the utility criterion.Key Points： Expectation criteria for risk-based decision-making; risk-based decision-making methodsDifficult Points：Chapter 10
48、Uncertain Decision-making (supporting course objectives * 2*)Basic concepts of uncertain decision-making11.1 Optimistic decision criteria11.2 Criteria for pessimistic decision-makingThe compromise decision criterion11.3 Equal probability decision criteriaRegret decision criteriaTeaching Requirements:Through the study in Chapter 11, students are required to be familiar with the basic concepts of uncertain decision-making; master the commonly used uncertain decision-making