代做CSCE 440编程、MATLAB程序设计代做

日期：2021-07-15 10:01

Numerical Analysis

CSCE 440/840 Final Project Spring 2021

This project can be done as a group project with two or three students in a group.

1. (15 points) Data Collection: Select any topic that you are interested in.

Regarding this topic find some suitable data. This could be any data of your

own, or published data from a book or journal, or some data downloaded from

any website. The size of the data should be neither too small nor too large.

Cite the source of your data including any webpage address.

2. (100 points) Experimental Comparison of Numerical Algorithms: Implement

(in MATLAB or another high-level programming language) at least two

alternative algorithms (or three for groups of three students) to process your

data. You can select algorithms from any of the following groups (as suitable

to your data):

(a) Function interpolation methods. [Open for undergraduates only]

(These include Lagrange Interpolation Method, Newton’s Divided Differences

Method, Piecewise Linear Interpolation, Piecewise Linear Approximation,

Piecewise Quadratic Interpolation, Cubic Spline Interpolation).

(Note: If you use Lagrange Interpolation or Newton’s Divided Differences

Method, which were implemented in an earlier homework, then you need

to implement two new methods beside those.)

(b) Spatial interpolation methods. (These include Shape Function Interpolation,

Inverse Distance Weighting, and Bezier Interpolation.)

(c) Numerical integration methods. (These include the Upper and Lower

Bound Sum of Rectangles Methods, the Trapezoid Method, Simpson’s

Method, Romberg’s Method, and the Monte Carlo Method.) In the comparison,

compare the accuracy using the same number of intervals and/or

the computational complexity.

(d) Methods of evaluating systems of linear equations. (These include

the naive Gaussian Method, and the Partial Pivoting Method.) In the

comparison of these methods, give the residual errors and the condition

numbers.

(e) Least squares approximation methods. (These include, linear, polynomial

and exponential least squares approximations.)

(f) Any other pair of numerical algorithms. (For example, root finding

methods. These need to be checked and approved by the instructor).

3. (25 points) Suppose your boss in a company asks you to evaluate the above

methods and write a summary and recommendation about which method to

use. In your slides, please include a summary of your computational experiments’

results. Present your findings in a table, bar chart, or other visual

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methods. Include in the comparison and discussion of any relevant information

about accuracy and computational complexity. Finally, include in your summary

a statement about which algorithm you would recommend to others and

the reason for your recommendation.

4. (10 points) Make a class presentation about your project using powerpoint

slides. Before you upload your final project to Canvas, record your presentation

separately and provide a link to your video. Earlier class videos can be found at:

https://www.youtube.com/playlist?list=PLGyluJ4a-mm7PHVFBLbuf2YECQmPGckcN

(Look at the second half of the listed projects. Some explicitly say ”440 class.”)

Note: The source code submitted should be executed on CSE server. Provide a

”README” file that describes the source code for each problem and indicates how

to compile and execute each of your programs.

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