Atmospheric Downscaling using Genetic Programming
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Title: | Main Title: Atmospheric Downscaling using Genetic Programming |
Description: | Abstract: We have implemented the strength Pareto approach for multi-objective fitness assignment into the GPLAB package. In the first chapter of this report we provide an overview of the added functions and most important changes. In the second chapter we describe set-up and test of the Pareto GP with three objectives on the problem of downscaling nightly near-surface temperature fields. As training data we have used instantaneous model output fields (not means over a whole night as in the previous report) and a wider range of weather conditions including days with rain and precipitation. The first test of the Pareto based GP gives promising results. Adjustment and expansion of the multiple objectives might allow further improvements. |
Responsible Party
Creator: | Tanja Zerenner (Author) |
Publisher: | CRC/TR32 Database (TR32DB) |
Publication Year: | 2014 |
Topic
TR32 Topic: | Atmosphere |
Related Subproject: | C4 |
Subject: | Keyword: PhD Report |
File Details
Filename: | report4_zerenner.pdf |
Data Type: | Text - Text |
File Size: | 5.6 MB |
Date: | Available: 18.02.2014 |
Mime Type: | application/pdf |
Data Format: | |
Language: | English |
Status: | Completed |
Constraints
Download Permission: | Only Project Members |
General Access and Use Conditions: | For internal use only. |
Access Limitations: | For internal use only. |
Licence: | [TR32DB] Data policy agreement |
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Specific Information - Report
Report Date: | 28th of August, 2013 |
Report Type: | PhD Report |
Report City: | Bonn, Germany |
Report Institution: | Meteorological Institute, University Bonn |
Number of Pages: | 8 (1 - 8) |
Further Information: | TR32 Student Report Phase II |
Metadata Details
Metadata Creator: | Tanja Zerenner |
Metadata Created: | 18.02.2014 |
Metadata Last Updated: | 18.02.2014 |
Subproject: | C4 |
Funding Phase: | 2 |
Metadata Language: | English |
Metadata Version: | V50 |
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Page Visits: | 783 |
Metadata Downloads: | 0 |
Dataset Downloads: | 5 |
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