On Impulsive Integrated Pest Management Models with Stochastic Effects

We extend existing impulsive differential equation models for integrated pest management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competin...

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Main Authors: Olcay eAkman, Timothy eComar, Daniel eHrozencik
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-04-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00119/full
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author Olcay eAkman
Timothy eComar
Daniel eHrozencik
author_facet Olcay eAkman
Timothy eComar
Daniel eHrozencik
author_sort Olcay eAkman
collection DOAJ
description We extend existing impulsive differential equation models for integrated pest management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competing stochastic components. This approach enables us to select a model with optimally determined weights for maximum accuracy and precision in parameter estimation. This is significant in the case of integrated pest management because the proposed model accommodates varying unknown environmental and climatic conditions, which affect the resources needed for pest eradication.
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spelling doaj.art-ca52bd8fd9704245a769317d89f3823a2022-12-22T03:19:21ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2015-04-01910.3389/fnins.2015.00119118919On Impulsive Integrated Pest Management Models with Stochastic EffectsOlcay eAkman0Timothy eComar1Daniel eHrozencik2Illinois State UniversityBenedictine UniversityChicago State UniversityWe extend existing impulsive differential equation models for integrated pest management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competing stochastic components. This approach enables us to select a model with optimally determined weights for maximum accuracy and precision in parameter estimation. This is significant in the case of integrated pest management because the proposed model accommodates varying unknown environmental and climatic conditions, which affect the resources needed for pest eradication.http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00119/fullIntegrated Pest Managementbirth pulsestochastic componentprobabilistic mixtureImpulsive differential equations
spellingShingle Olcay eAkman
Timothy eComar
Daniel eHrozencik
On Impulsive Integrated Pest Management Models with Stochastic Effects
Frontiers in Neuroscience
Integrated Pest Management
birth pulse
stochastic component
probabilistic mixture
Impulsive differential equations
title On Impulsive Integrated Pest Management Models with Stochastic Effects
title_full On Impulsive Integrated Pest Management Models with Stochastic Effects
title_fullStr On Impulsive Integrated Pest Management Models with Stochastic Effects
title_full_unstemmed On Impulsive Integrated Pest Management Models with Stochastic Effects
title_short On Impulsive Integrated Pest Management Models with Stochastic Effects
title_sort on impulsive integrated pest management models with stochastic effects
topic Integrated Pest Management
birth pulse
stochastic component
probabilistic mixture
Impulsive differential equations
url http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00119/full
work_keys_str_mv AT olcayeakman onimpulsiveintegratedpestmanagementmodelswithstochasticeffects
AT timothyecomar onimpulsiveintegratedpestmanagementmodelswithstochasticeffects
AT danielehrozencik onimpulsiveintegratedpestmanagementmodelswithstochasticeffects