Effective Stochastic Algorithm in Disease Prediction.
Adv Exp Med Biol
; 1194: 293-301, 2020.
Article
em En
| MEDLINE
| ID: mdl-32468545
ABSTRACT
Traditionally, the main process for olive fruit fly population monitoring is trap measurements. Although the above procedure is time-consuming, it gives important information about when there is an outbreak of the population and how the insect is spatially distributed in the olive grove. Most studies in the literature are based on the combination of trap and environmental data measurements. Strictly speaking, the dynamics of olive fruit fly population is a complex system affected by a variety of factors. However, the collection of environmental data is costly, and sensor data often require additional processing and cleaning. In order to study the volatility of correlation in trap counts and how it is connected with population outbreaks, a stochastic algorithm, based on a stochastic differential model, is experimentally applied. The results allow us to predict early population outbreaks allowing for more efficient and targeted spraying.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças das Plantas
/
Algoritmos
/
Tephritidae
/
Olea
/
Agricultura
/
Modelos Biológicos
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Revista:
Adv Exp Med Biol
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Grécia