# 计算机建模作业代写｜FIT3139 2023-S1: Final project

## 这是一篇来自澳洲的关于计算机建模作业代写，具体作业要求是：解释和应用计算科学模型的建立、验证和解释的过程；分析建模方法的核心类别之间的差异（数值与分析；线性与非线性；连续与离散；确定性与随机性）；评估选择不同的建模方法的含义；合理化模拟和数据可视化在科学中的作用；将以上所有内容应用于解决跨各种科学学科的现实世界问题的理想化，以下是作业部分内容：

To demonstrate all learning outcomes, you will develop an extension of a model discussed in the classroom. An extension addresses the same problem, but adds or relaxes specific assumptions about the model. For example, taking a deterministic model and introducing assumptions to do a stochastic analysis,or providing stochastic analysis for a simulation.

Your extension should address the same problem, but contain some different assumptions that may or may not lead to different conclusions — an analysis should be presented comparing the results of the original model and the extended model. The model extension should be explained, interpreted an analysed,and it should allow you to showcase at least two of the following techniques:

• Markov chains
• Montecarlo simulation
• Heuristics
• Game theory

Your extension should address two different modelling questions, and use the algorithms, techniques and visualisations discussed in the clasroom to answer those questions.

Submission structure

Report structure

Your report should contain the following sections:

Section 1: Specification table

Fill the following table.

Important: This table should be briefly discussed and signed by your demonstrator on week 11 and week 12, during the lab session – not via email or forum post, please plan accordingly.

Section 2: Introduction

• Learning outcomes 1, 5. 10% of project final mark
• Identify the problem you want to solve and its motivation, describe what the extension will be and identify questions your model will answer. In other words, this section takes the information in the specification table and develops it providing more detail and a motivation of your questions, and how your techniques are appropriate.
• Write clearly. Your mark is based on what we can understand so spend time crafting the text.

Section 3: Model description

• Learning outcomes 1, 2, 5. 35% of project final mark
• Specify model extension details and list assumptions for both the original model and the extension model. Determine the class of model and analysis you are presenting (Numerical versus Analytical;Linear versus Non-linear; Continuous versus Discrete; Deterministic versus Stochastic). Be sure to describe in detail any algorithms or mathematical results or derivations you may use.
• Be clear and help the reader as much as you can.

Section 4: Results

• Learning outcomes 2, 3, 4, 5. 35% of project final mark
• Interpret and analyse the results of your extended model, including visualisation of results. You should explain how you arrive at your results. All figures should be discussed, explained and interpreted and your report should include at least 3 Figures. The results and figures should support how you are answering the questions you have chosen to answer.
• Be clear and help the reader as much as you can.

Section 5: List of algorithms and concepts

• Learning outcomes 2, 5. 5% of project final mark
• List of algorithms and concepts used in the unit that play a role in your model and interpretation.

Video presentation

You should submit a presentation where you discuss your extended model. The presentation should be no longer that 10 minutes, and use slides to enhance the description of the model and the explanation of your results. It is suggested the presentation keep a similar structure to that of the report. The presentation is worth 15% of project final mark.

A simple procedure to record the presentation using zoom can be found here: https://www.youtube.com/watch?v=P6cTbnUPwfY

Source code

All code should be submitted and appropriately commented. It will be checked for correctness and be part of the marking in the model section (if the code is used to produce results, or in the results section if the code is used to analyze results). Clarity is in your best interest.

You can use any of the standard libraries we used in the class as long as you can explain what the library is doing.

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