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|Title:||Comparison of nature-inspired algorithms||Authors:||Tham, Choon Fai||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence||Issue Date:||2015||Abstract:||This report is written to conclude my project titled 'Comparison of Natureinspired Algorithms'. As titled, the main purpose of this report is about these comparisons. The algorithms I will be covering in this report will be Genetic Algorithm, Particle Swarm Optimization and Ant Colony Algorithm. Since I have no exposure to these algorithms, I find that even understanding them and their purpose to be somewhat difficult. As such, I will be using a lot of analogy, examples to try to express what I understand of these algorithms to be. There will be an explanation to these algorithms and the basis of their inspiration. The general steps involved will also be mentioned. However, the many many different variations for them will not be covered. The conclusion of these algorithms will be obtained via GNU Octave which is a freeware similar to Matlab. As Octave is based on Matlab, I believe it should not pose much of a problem when reenacting on the Matlab program itself. The programs I have written and used for the testing will also be included and an explanation of though process and purpose will also be explained.||URI:||http://hdl.handle.net/10356/65769||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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