Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
404118 | Knowledge-Based Systems | 2008 | 8 Pages |
Abstract
This paper studies the problem of predicting future values for a number of water quality variables, based on measurements from under-water sensors. It performs both exploratory and automatic analysis of the collected data with a variety of linear and nonlinear modeling methods. The paper investigates issues, such as the ability to predict future values for a varying number of days ahead and the effect of including values from a varying number of past days. Experimental results provide interesting insights on the predictability of the target variables and the performance of the different learning algorithms.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Evaggelos V. Hatzikos, Grigorios Tsoumakas, George Tzanis, Nick Bassiliades, Ioannis Vlahavas,