Identification

Title

Optimizing Genetic Algorithm Parameters for Atmospheric Carbon Monoxide Modeling

Abstract

A main source of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere is large burn events, making CO a useful proxy for fires. Therefore, predictive CO models over fire regions can help countries prepare for unusually large fire seasons. Fires are related to the climate through fuel dryness and availability, both of which respond to variability in the climate. Climate indices are metrics that summarize climate variability through changes in sea surface temperature and wind. In previous work, we developed a multiple linear regression model that uses these climate indices to predict atmospheric CO and created the R package regClimateChem to perform variable selection. This package offers three different variable selection techniques: stepwise selection, a genetic algorithm, and an exhaustive search. The exhaustive search always finds the best possible model but is computationally expensive. Stepwise selection runs quickly and is scalable but often fails to find the best model. We implement a genetic algorithm as a potential compromise between computational expense and model accuracy. As a stochastic variable selection technique, the genetic algorithm has many parameters that affect the stopping criterion, frequency of the model modification techniques, and population size. Here we present a parameter optimization study for the genetic algorithm, seeking to balance computational expense and model quality. When considering models with four covariates, we find that the optimized genetic algorithm parameters result in a runtime reduction of 11.8% and only compromise 0.3% accuracy compared to the default settings. We then consider models with five covariates using a high-performance computing system. For models with five covariates, we find that the optimized population size becomes close to the total number of models, meaning it behaves similarly to the exhaustive method

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7df6vng

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Keyword set

keyword value

EARTH SCIENCE SERVICES > DATA ANALYSIS AND VISUALIZATION > STATISTICAL APPLICATIONS

EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL IMPACTS > BIOMASS BURNING

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY > CARBON AND HYDROCARBON COMPOUNDS > ATMOSPHERIC CARBON MONOXIDE

EARTH SCIENCE > ATMOSPHERE > AIR QUALITY > CARBON MONOXIDE

originating controlled vocabulary

title

reference date

date type

revision

effective date

2021-09-17

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2021-06-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Copyright Author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata date

2023-08-18T18:06:39.727046

Metadata language