Paper · 2003 · International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003

Multipopulation genetic programming for forecasting crop pests

Lijue Tang; Miao Li; Jian Zhang

3
claims
6
verbatim quotes
3
citations
2
research areas
—
Not open access

Abstract

This contribution attempts to study on forecasting crop pests with multipopulation genetic programming (MGP). In our previous work, standard genetic programming (SGP) evolves a single population, which often results in premature convergence. This paper concentrates on multipopulation evolution in order to maintain population diversity to avoid this. Comparison between single and multi population shows superiority of the latter. Study of migration interval and migration rate draws the conclusion that it is helpful to obtain optimal solutions that subpopulations keep communicating often and only a few of individuals migrate when communicating. All experiments are based on forecasting wheat stripe rust disease. MGP shows good prediction, which is hopeful to become an auxiliary method for forecasting crop pests.

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Claims 3

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Multipopulation genetic programming outperformed single-population genetic programming for forecasting wheat stripe rust.

Interactor
stripe ruste2pathogen
Outcome
superioritye1
Direction
superioritye1
Comparator
singlee1

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e2

“All experiments are based on forecasting wheat stripe rust disease”

✓ located verbatim in the source · abstract, characters 650–716 · show in text ↑
e1

“Comparison between single and multi population shows superiority of the latter”

✓ located verbatim in the source · abstract, characters 352–430 · show in text ↑
Recommendationauthor interpretationoriginal resultbasis n/a

Claim · model-written summary

Frequent communication between subpopulations with only a few migrating individuals gives optimal solutions in wheat stripe rust forecasting.

Outcome
keep communicating oftene3

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e2

“All experiments are based on forecasting wheat stripe rust disease”

✓ located verbatim in the source · abstract, characters 650–716 · show in text ↑
e3

“Study of migration interval and migration rate draws the conclusion that it is helpful to obtain optimal solutions that subpopulations keep communicating often and only a few of individuals migrate when communicating”

✓ located verbatim in the source · abstract, characters 432–648 · show in text ↑
Observationobservedoriginal resultpositivemeasured

Claim · model-written summary

Multipopulation genetic programming shows good prediction of wheat stripe rust.

Outcome
predictione4
Qualifier
goode4

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e2

“All experiments are based on forecasting wheat stripe rust disease”

✓ located verbatim in the source · abstract, characters 650–716 · show in text ↑
e4

“MGP shows good prediction”

✓ located verbatim in the source · abstract, characters 718–743 · show in text ↑