ERA

Download the full-sized PDF of Modeling zooplankton diel vertical migration patterns based on curve fitting and feature correlation analysisDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3FX2Z

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Modeling zooplankton diel vertical migration patterns based on curve fitting and feature correlation analysis Open Access

Descriptions

Other title
Subject/Keyword
feature correlation analysis
curve fitting
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhao, Shuang
Supervisor and department
Joerg Sander (Computing Science)
Examining committee member and department
Sally Leys (Biological Sciences)
Osmar R. Zaiane (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2010-01-07T18:54:37Z
Graduation date
2010-06
Degree
Master of Science
Degree level
Master's
Abstract
The goal of this thesis is to study and model the Diel Vertical Migration (DVM) pattern using machine learning methods. We choose an Almost Periodic Function as the mathematical model and fit the monthly averaged migration data into a 5-term Fourier series whose coefficients and frequency are functions of time. The resulting function captures the general characteristics of the DVM pattern whose period is similar yet undergoes gradual changes over time. Further correlation analyses show that the monthly averaged distribution of zooplankton and various environmental factors are strongly correlated. Therefore, we adjust the function so that the coefficients and frequency are functions of environmental factors. Besides, we also examine the pattern on finer time scales using classification algorithms. We build classifiers which predict zooplankton existence at different depths based on a set of environmental measurements. Experiments demonstrate that both of the above methods are valid in modeling the DVM pattern.
Language
English
DOI
doi:10.7939/R3FX2Z
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication

File Details

Date Uploaded
Date Modified
2014-05-01T02:20:55.013+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 2524128
Last modified: 2015:10:12 17:21:50-06:00
Filename: Zhao_Shuang_Spring 2010.pdf
Original checksum: 3d5ec5228eb2a202fbdbf6811c5a93b7
Well formed: true
Valid: true
Page count: 101
Activity of users you follow
User Activity Date