Difference between revisions of "User:Eg142"
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===Grand Challenges for Engineering=== | ===Grand Challenges for Engineering=== | ||
[http://www.ni.com/newsletter/51760/en/ Making Solar Energy Economical], National Instruments, Created June 04 2013, Accessed September 21 2017 (Making Solar Power Economical) | [http://www.ni.com/newsletter/51760/en/ Making Solar Energy Economical], National Instruments, Created June 04 2013, Accessed September 21 2017 (Making Solar Power Economical) | ||
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| + | ===MatLab Demos=== | ||
| + | My favorite out of the '''MatLab Demonstrations''' for Homework 2 was the '''Traveling Salesman Problem''' animation. This is a problem that I learned about when I was first leaning about computers. The problem has been described to me as the perfect example of a problem requiring a heuristic solution because it would be nearly impossible to calculate the perfect route for the salesman to use. For this reason, I find it extraordinarily interesting to watch the computer work out the solution piece by piece, taking more time when more cities are added to the puzzle. | ||
Latest revision as of 00:55, 22 September 2017
About Me
I am a student in the Pratt School of Engineering. I am planning on majoring in ECE with a double minor in energy and Spanish.
Interests
I am particularly interested in renewable energy and plan to study ECE with an emphasis in electrical engineering.
Grand Challenges for Engineering
Making Solar Energy Economical, National Instruments, Created June 04 2013, Accessed September 21 2017 (Making Solar Power Economical)
MatLab Demos
My favorite out of the MatLab Demonstrations for Homework 2 was the Traveling Salesman Problem animation. This is a problem that I learned about when I was first leaning about computers. The problem has been described to me as the perfect example of a problem requiring a heuristic solution because it would be nearly impossible to calculate the perfect route for the salesman to use. For this reason, I find it extraordinarily interesting to watch the computer work out the solution piece by piece, taking more time when more cities are added to the puzzle.
