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MCM/ICM数学建模竞赛 第3卷

样章
作者：
Jay Belanger等
定价：
59.00元
ISBN：
978-7-04-049121-0
版面字数：
310.000千字
开本：
16开
全书页数：
暂无
装帧形式：
平装
重点项目：
暂无
出版时间：
2018-01-26
读者对象：
学术著作
一级分类：
自然科学
二级分类：
数学与统计
三级分类：
通用
暂无
  • 前辅文
  • 1 Writing for Winning
    • Jie Wang
    • 1.1 Paper Evaluations
    • 1.2 Tell A Good Story
    • 1.3 Tell the Story Well
    • 1.4 Sensitivity Analysis Is a Must
    • 1.5 Write Well
    • Exercises
    • References
  • 2 A Hot Bath
    • Jay Belanger
    • 2.1 Problem Description
    • 2.2 Outstanding Winners
    • 2.3 Previous Work
      • 2.3.1 Classic formulas
      • 2.3.2 Bathtub measurements
      • 2.3.3 Previous work on water cooling
    • 2.4 Approaching the Problem
    • 2.5 Models
      • 2.5.1 Assumptions and justifications
      • 2.5.2 Functions and parameters
      • 2.5.3 Determining the heat loss
      • 2.5.4 Preserving heat
      • 2.5.5 Heat dispersal
      • 2.5.6 Answering the main question
      • 2.5.7 Other questions
      • 2.5.8 Results
    • 2.6 Sensitivity Analysis
    • 2.7 Strengths and Weaknesses
      • 2.7.1 Strengths
      • 2.7.2 Weaknesses
    • 2.8 Comments
    • Exercises
    • References
  • 3 Space Junk
    • Jay Belanger
    • 3.1 Problem Description
    • 3.2 Outstanding Winners
    • 3.3 Previous Work
      • 3.3.1 Kessler's work
      • 3.3.2 Debris removal methods
      • 3.3.3 Political obstacles
      • 3.3.4 Business opportunities
    • 3.4 Approaching the Problem
    • 3.5 A Continuous Approach
      • 3.5.1 How to approach the problem
      • 3.5.2 Assumptions and justifications
      • 3.5.3 Modeling details
      • 3.5.4 Results
    • 3.6 A Probabilistic Approach
      • 3.6.1 How to approach the problem
      • 3.6.2 Assumptions and justifications
      • 3.6.3 Modeling details
      • 3.6.4 Results
    • 3.7 Sensitivity Analysis
    • 3.8 Strengths and Weaknesses
      • 3.8.1 Strengths
      • 3.8.2 Weaknesses
    • 3.9 Comments
    • Exercises
    • References
  • 4 The Goodgrant Challenge
    • Robert E. Burks, Rodney X. Sturdivant
    • 4.1 Problem Description
    • 4.2 Outstanding Winners
    • 4.3 Previous Work
      • 4.3.1 Bill and Melinda Gates Foundation
      • 4.3.2 Lumina Foundation
      • 4.3.3 Principal component analysis
      • 4.3.4 Analytic hierarchy process
    • 4.4 Modeling Approach
      • 4.4.1 Thinking about the problem
      • 4.4.2 Assumptions
      • 4.4.3 Data analytics
      • 4.4.4 Selecting metrics of success
      • 4.4.5 Return on investment
    • 4.5 Modeling Approach
    • 4.6 Sensitivity Analysis
    • 4.7 Strengths and Weaknesses
      • 4.7.1 Strengths
      • 4.7.2 Weaknesses
    • 4.8 Comments
    • Exercises
    • References
  • 5 Measuring the Evolution and Influence in Society's Information Networks
    • Jessica Libertini, Ralucca Gera
    • 5.1 Problem Description
    • 5.2 Outstanding Winners
    • 5.3 Approaching the Problem
    • 5.4 Diffusion Networks
      • 5.4.1 Basic assumptions and justification
      • 5.4.2 Defining ``news''
      • 5.4.3 Previous work
      • 5.4.4 Results
      • 5.4.5 Exploring the future of communication
      • 5.4.6 Sensitivity analysis
      • 5.4.7 Conclusions, strengths, weaknesses, and future work
    • 5.5 Modeling Communication Using Disease Models
      • 5.5.1 The information circulation network
      • 5.5.2 The news filter model
      • 5.5.3 Testing and using the NF model
      • 5.5.4 The information circulation network prediction model
      • 5.5.5 The public interest and information network interaction model
      • 5.5.6 Sensitivity analysis
      • 5.5.7 Strengths and weaknesses
    • 5.6 Comments
    • Exercises
    • References
  • 6 Are We Heading Towards A Thirsty Planet?
    • Amanda Beecher, Amy Richmond
    • 6.1 Problem Description
    • 6.2 Outstanding Winners
    • 6.3 Previous Work
    • 6.4 A Three-pronged Interdisciplinary Modeling Approach
      • 6.4.1 Approach to the problem
      • 6.4.2 Case study: the water problem in Haiti
      • 6.4.3 Assumptions and justifications
      • 6.4.4 System-network model
      • 6.4.5 Algorithmic model
      • 6.4.6 Agent-based network model
      • 6.4.7 Intervention plan
      • 6.4.8 Sensitivity analysis
      • 6.4.9 Strengths and weaknesses
    • 6.5 A Flow Model based on Time-Constrained Water Use
      • 6.5.1 Model development
      • 6.5.2 Case study: water scarcity in Egypt
      • 6.5.3 Model adaption
      • 6.5.4 Results
      • 6.5.5 Intervention
    • 6.6 Comments
    • Exercises
    • References
  • 7 Modeling Refugee Immigration Policies
    • Evelyn Panangkou, Yulia Tyshchuck, Christian Nattiel, Don Stanley Dalisay, Kate Coronges
    • 7.1 Current Refugee Problems
    • 7.2 Problem Description
    • 7.3 Outstanding Winners
    • 7.4 How to Approach the Problem
    • 7.5 Empirical Policy Research
    • 7.6 Identify Parameters and Develop Metrics
    • 7.7 Modeling Approaches to Policy Problem
      • 7.7.1 Assumptions
      • 7.7.2 Static modeling approach
      • 7.7.3 Dynamical modeling approaches
    • 7.8 Sensitivity Analysis
      • 7.8.1 Scalability
      • 7.8.2 Robustness
      • 7.8.3 Uncertainty
    • 7.9 Policy Recommendations
    • 7.10 Strengths and Weaknesses
    • 7.11 Judges' Comments by Task
    • Exercises
    • References
  • 8 Complex Event and Pattern Models in Sequence Data Processing
    • Tingjian Ge, Yan Li, Cindy Chen
    • 8.1 Introduction and Problem Description
      • 8.1.1 Windowed subsequence matching
      • 8.1.2 Extended regular expressions
      • 8.1.3 Event patterns with graph structure
    • 8.2 Formal Definition of Pattern Models
      • 8.2.1 Windowed subsequence
      • 8.2.2 Extended regular expressions
      • 8.2.3 Event pattern with graph structure
    • 8.3 Error Models
    • 8.4 Matching Algorithms
      • 8.4.1 Algorithms for windowed subsequence matching
      • 8.4.2 Algorithms for extended regular expression matching
      • 8.4.3 Algorithms for event pattern with graph structure
    • Exercises
    • References
  • Index

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