Graduation Semester and Year

2012

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Jean Gao

Abstract

Because of the larger data storage and the faster computational power, computer can process and store much finer resolution data. Aside from data analysis, data visualization is also an important task to understand the data. In this work, the Hydrological Visualization and Analysis System is developed to help both hydrologists and local people view and examine the high resolution hydrological data. Then, this data is analyzed to determine which variables are related to the change of drought condition in Arlington, Texas. A new correlation measurement method called sectional correlation is proposed and used as an objective function of the drought related feature selection. The proposed sectional correlation algorithm has good performance in terms of computational efficiency and the accuracy. The result error is quite low, about 2% of the range of value.

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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