Features
Features:

Product Tour >

Edraw AI >

Paid Plans:

Individuals >

Business >

Eduaction >
Resources
Blog

History

How-tos & Tips

Discovery

Biography

Business Analysis

Examples

AI concept Map

Free AI Mind Map Generator

Onenote Mind Map

Bcg Matrix Examples

Nike Marketing Strategy

Unilever SWOT Analysis

Make Mind Maps in Google Docs

Guide

FAQs

What's New

Resource Center
Templates
All Templates

Brain Storming Templates

Strategy and Planning Templates

Project Management Templates

Product Management Templates

Human Resources Templates

Agile Workflow Templates

Marketing Templates

Education Templates

Fun and Games Templates

User Gallery
Download
Pricing
Enterprise

MindMap Gallery Guidance for the American College Student Mathematical Modeling Competition

Guidance for the American College Student Mathematical Modeling Competition

Many teams relied on this set of pre-match tutorials to win M or F awards. This template introduces in detail the process of the American College Student Mathematical Modeling Competition, tips for each stage before, during and after the competition, and the data processing software involved. Document search tools, translation tools, etc. It is recommended that all team members study together before the competition, which can greatly increase the probability of winning.

Edited at 2024-03-02 22:40:59

PlotWizard

Recent works View more works>>

Guidance for the American College Student Mathematical Modeling Competition

PlotWizard

Recent works View more works>>

Recommended to you
Outline

differential equation model
- 17
PlotWizard

US Sai Guidance

Basic introduction to mathematical modeling

Precautions

Not participating in online discussion groups

Do not use model diagrams and programs that were not completed by yourself

Protect your papers from leakage and prohibit plagiarism checking and translation

What is mathematical modeling

Use mathematical language and methods to abstractly simplify and establish a path that can approximately describe and solve the problem.

Actual problems are expressed as mathematical models, and the mathematical models are solved to achieve and verify answers to actual problems.

Enter mathematical modeling

Learn the basics of math

Calculus, linear algebra, modern algebra, analytic geometry, differential geometry, ordinary differential equations, probability theory, mathematical statistics, mathematical modeling

Participate in on-campus mathematical modeling competitions

Practice is the only way to transform book knowledge into your own abilities

Participate in the National Undergraduate Mathematical Modeling Competition

Second week of fall semester

Apply for undergraduate research projects, graduation thesis design, Shenzhen Cup Challenge, Jiangsu Big Data Development and Application Competition, American College Student Mathematical Modeling Competition

Abilities developed by participating in mathematical modeling competitions

Discover and ask mathematical questions from real problems

Ability to quickly acquire information and master new knowledge through literature reading

Abstractly define mathematical concepts, set variables and parameters, and determine solution goals

Choose appropriate mathematical methods and establish mathematical models

Not only can you deductively reason, program and calculate, and be familiar with mathematical software

Bold and careful, perseverant, confident and self-reliant

Master the writing methods of scientific papers, write rigorously and express clearly

Have teamwork awareness and spirit

Basic process of mathematical modeling

Read the question, understand the actual problem situation, and clarify the key points and goals of the problem

What do you want?

What is the purpose?

What factors are involved?

Must be discussed clearly before reviewing the literature

Translation, extracting mathematical problems from practical problems

Model, select variables, adopt or construct appropriate mathematical models

Solving, using mathematical reasoning and programming calculation methods to solve mathematical models

Test, compare the results of the mathematical model with the actual situation, and verify the model results

Explain, analyze the limitations and scope of application of mathematical models, and provide conclusions to solve practical problems

The first element of mathematical modeling: mathematical definition

Introduce mathematical definitions and determine variables and parameters

Only with mathematical definitions can we have mathematical models

Analyze variable relationships and select appropriate mathematical models

The second element of mathematical modeling: reasonable assumptions

Define uncertain factors, replace complexity with simplicity, and make up for the lack of information.

Assumptions need to strike the right balance between practicality and mathematical simplicity

Conclusions based on assumptions must undergo parameter sensitivity analysis and model robustness analysis

Clearly describe the rationality, necessity and impact of the assumptions, give reasons, cite literature, and analyze the implications.

The third element of mathematical modeling: focus on reality

Establish the model based on reality, model mathematical reasoning with the help of reality, and finally use reality to test the model

Key points for preparation for mathematical modeling competition

U.S. competition rules and precautions

2.5 5 a.m. - 2.9 8 a.m. (ends at 9 a.m.)

4.1 Result

The total number of pages should not exceed 25 pages

Abstract, Table of Contents, References, Appendix

Team serial number

Communication outside the team is strictly prohibited

Reference standards, pictures too

Do not disclose personal information

Minimum font size 12

Download thesis template

Submit email: solutions@comap.com

File name (only one pdf), subject is team serial number

The home page is an abstract, only one pdf, no personal information.

Upload papers three hours in advance

Protect the credit card used for payment and print and save the payment invoice

Registration and team formation

The paper must be written by three people together and takes at least one and a half days.

In order to write a clear paper, I would rather choose a simpler model

Preparation before the game

Software preparation

Matlab, Netlogo, spss, r, python, arcgis, drawing software

Model preparation

Partial differential equation model A

Differential Equation Model B

Statistical model C

Optimization model ABCDEF

Simulation model ABD

Algorithm preparation

Algorithm A for numerical solution of partial differential equations

Discrete Model Simulation Algorithm B

Parameter estimation method C

Stochastic intelligent optimization algorithms (simulated annealing, genetic algorithms) neural networks, machine learning

Learn how to do model testing, sensitivity analysis

Literature search tools: Google, CNKI, Muduo search

Translation tools

CNKI's scientific and technological English translation

Read excellent papers

On-campus resources

Writing skills practice, prepare essay template

word,latex

Prepare 3 computers and install relevant software

Read the competition rules carefully, summarize the most important essay writing notes, and post them in a conspicuous place

Select past competition questions for simulation practice

Training problem analysis and review skills

Learn how to model testing, especially sensitivity analysis

Writing skills practice

Form a team cooperation model and be familiar with the basic procedures for selecting topics, discussing, solving problems, and writing

Characteristics of US Contest Questions

Key points of the modeling competition

Topic selection

Choose the direction you are most familiar with

The apparent difficulty is not necessarily the same as the actual difficulty

Carefully analyze the logical connections between various small problems

Draw all the key words in the question, taking into account

Determine the computational complexity of the model

Determine the possibility of innovation

Blindly copying documents

Follow others' opinions

Poor understanding of the problem

Weak quantitative skills

Information search

Model selection

Reasonableness of conclusion

computer aided

essay writing

Scoring method

No more than a few points without considering any factors

Completeness, strict logic, clear expression, transcending phenomena to see the essence, easy to read and understand, and standardized citations

step

Problem analysis, insight into the theme

what is the goal

What are you asking for and how are the issues related?

What are the main influencing factors and put forward hypotheses

Read the question carefully

What models can be used

What literature to draw from

Notes on essay writing

Key indicators of paper quality

Correct application of mathematical methods

Completeness and depth of problem solving

Innovative and insightful modeling methods

Clear and concise text description

Visual presentation of results

Common mistakes

There are too many symbols, and there is no symbol explanation under the main model.

Irregular literature citation

There is no derivation process, no formula symbols, and I don’t know where the results will come from.

There are too many excerpts from the literature, and the duplication check exceeds the limit.

The chart formula is not clear

Failure to use charts and graphs to express results clearly and concisely

Only numerical results, no algorithms, no algebraic models

Separate model and solution process

Do not express the results in the text, or even have no results at all

Other things to note

Fonts should be coordinated

Don’t use weird fonts

Don’t use picture formulas

Check whether the formula has been blurred

Say important things more than three times

Avoid typos and grammatical errors in important places

Charts and charts should be numbered separately and have descriptions. The descriptions of the figures are below and the descriptions are above.

Important symbols are always explained

Literature citation is very important, especially when the background theory of the problem is relatively advanced, you must also clearly point out your own improvements and processing.

Clearly write down what a certain document did using this method, and what we did using or improving this method.

Regardless of whether it can be calculated or not, there must be a process and result.

The results obtained must be vivid and colorful, and the graphs and text should be combined to explain the rationality.

Must master drawing software

The paper must be written by three people together

Basic paper format

topic

summarysummary

Be concise, no background to the question, no more than one page

What model was built for what problem, what algorithm was used to get what conclusion, the innovation lies in

Write in paragraphs according to questions

No formulas, literature references, or symbols should appear.

Never make it up

keywordkeyword

Professional vocabulary for research objects and research methods

Table of contents

Text part

1. Problem restatement and analysis

Proposition of the problem and its background, emphasis on key points and solutions, data description, literature review (where to get inspiration or which methods mentioned in the literature are not used)

What amount do you want?

What is the goal? What is the significance of research?

What are the relevant factors? elicit the following hypothesis

What is the key point in solving the problem? elicit problem-solving methods

Full-text review of modeling ideas, description of model algorithms, and article structure layout (emphasis on the characteristics and innovation of ideas and methods, and a brief review of the corresponding literature based on the problem)

Review the literature used, summarize the full text, and outline the model algorithm.

Don't copy the questions, otherwise you will be checked for plagiarism and explode.

Describe the problem objectives and solutions to the problem

The goal should be quantified into what quantity, and the method should be quantified into a specific mathematical model. Introduction to the models in the literature

Pay attention to the core goals of the analysis problem

Pay attention to the logical connections between tasks

Pay attention to flexible and dialectical analysis of problems, adapt to changes, and do not think in a fixed way

Think about the problem from the perspective of the person who asked the question, be immersed in the situation, and proceed from reality

2. Assumptions & justifications

Simplify and clarify the assumptions of the problem, reference parameters, and symbols of variables (don’t write too long, it will be explained later)

Simplify the problem appropriately

Make up for the lack of information and data

Must match model

Generally, assumptions about the parameters in the model

a hypothesis and a reason

3. Model construction and application

A clearly labeled model. The model must be consistent with the assumptions, the reasoning and calculations are clearly expressed, and there are clear mathematical conclusions and problem conclusions.

Model building

Preliminary data processing

Write clearly the derivation process and mathematical expressions of the model. There needs to be an explanation of the symbols below the main model.

When using classic models in the literature, do not copy the derivation process. Just provide explanations and citations.

Do not cite model principles in literature at large lengths

The mathematical form of the model must be present and cannot be written in pure text.

Reasons, derivation, detailed explanation, cited sources

Classification

Contour model

Dimensional model, scale model, interpolation, fitting

Mechanism model (partial differential equations, difference equations)

System of difference equations, detailed explanation, rationality

Differential equations, detailed derivation process

Detailed model building process

Optimization model

Optimization goals and constraints

Why use such constraints and why have such an objective function?

statistical model

Pay attention to the mathematical expression of random factors (random variable, distribution, expectation, variance)

Parameter estimation is the key

Model applicable conditions

Charts output by statistical software cannot be placed directly in the text. You must select useful results and re-table them.

Simulation model (cellular automaton)

Simulation rules are models

Do not use AHP unless necessary

Model calculation

The first step is to estimate and select the initial values and parameters in the model.

Write clearly the estimation method and reasons for selection

Secondly, briefly introduce the software used, the name of the algorithm, and the calculation time. Do not copy the algorithm principles in the literature.

Briefly describe the algorithm process and steps for important core algorithms in your own words, draw a simple and easy-to-read flow chart or use a ready-made toolbox software package

A statement of the data used in the calculation

The algorithm is very simple, even if you use a calculator to calculate it, you have to explain it.

Don't deliberately choose complex algorithms, everything is aimed at solving problems and making them easy to calculate, read and understand.

There is no need to attach code. For complex algorithms, try to choose ready-made software and toolboxes, and explain the input and output clearly.

results and analysis

The results are presented in various forms and are visualized

Data tables, prison sentences are best available

Don’t let people look at the pictures and speak for themselves. There must be lengthy explanations and descriptions of the results.

Pay attention to the description and number of the icon. The description of the figure is in the table below and centered. The font size in the figure is preferably half a size smaller than the main text.

4. Model testing and sensitivity analysis

Utilize data inspection and parameter sensitivity analysis

Model result testing, error analysis

Sensitivity analysis of model parameters, each parameter is analyzed

It is actually a test of the hypothesis

5. Further discussion (advantages, disadvantages and prospects) analysis of strengths&weaknesses

Advantages of the model, scope of use, possible improvements to the model

Just a formality

Model scope of application

Model improvements

6. Letter memo

Written based on the model result data, it is pragmatic and realistic for practical problems.

Must be placed before the reference

Just one page

References

Reference format

Modeling papers must have references

There must be literature citations in the text

superscript

appendix

Program code output results

Full model calculation results that are too large

The results output directly from the software operation, usually in the form of a table

Appendix appendix (programs and data) is optional