Please use this identifier to cite or link to this item:
http://hdl.handle.net/2067/48864
DC Field | Value | Language |
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dc.contributor.author | Rossello, Nicolas Bono | it |
dc.contributor.author | Rossini, Luca | it |
dc.contributor.author | Speranza, Stefano | it |
dc.contributor.author | Garone, Emanuele | it |
dc.date.accessioned | 2023-01-06T18:39:29Z | - |
dc.date.available | 2023-01-06T18:39:29Z | - |
dc.date.issued | 2022 | it |
dc.identifier.uri | http://hdl.handle.net/2067/48864 | - |
dc.description.abstract | This paper introduces an observer-based scheme to estimate pest populations in agricultural fields. The proposed scheme describes the different stages of the life cycle of insects as a system of ODEs and it uses an Extended Kalman Filter with intermittent observations to provide a state estimation. This scheme aims at providing a general framework to formally combine physiologically-based models and field measurements, contrary to current best practices where both methodologies are used independently in parallel. The presented approach allows to apply this framework to a large number of species of agricultural interest and to take advantage from different counting systems. The improvement of the presented approach with respect to current best practices is demonstrated by means of numerical simulations based on the case of Drosophila suzukii. | it |
dc.format.medium | ELETTRONICO | it |
dc.language.iso | eng | it |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | State Estimation of Pest Populations subject to Intermittent Measurements | it |
dc.type | conferenceObject | * |
dc.identifier.doi | 10.1016/j.ifacol.2022.11.128 | it |
dc.identifier.scopus | 2-s2.0-85144819148 | it |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S2405896322027616 | it |
dc.relation.journal | IFAC-PAPERSONLINE | it |
dc.relation.ispartofbook | 7th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture AGRICONTROL 2022 | it |
dc.relation.firstpage | 135 | it |
dc.relation.lastpage | 140 | it |
dc.relation.conferencename | 7th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture, AGRICONTROL 2022 | it |
dc.relation.conferenceplace | Munich | it |
dc.relation.conferencedate | 14-16 settembre 2022 | it |
dc.relation.volume | 55 | it |
dc.subject.scientificsector | AGR/11 | it |
dc.description.numberofauthors | 4 | it |
dc.description.international | sì | it |
dc.contributor.country | ITA | it |
dc.contributor.country | BEL | it |
dc.type.referee | REF_1 | it |
dc.type.invited | no | it |
dc.type.miur | 273 | * |
dc.publisher.name | Kidlington : Elsevier Ltd | it |
item.fulltext | With Fulltext | - |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.journal.journalissn | 2405-8963 | - |
crisitem.journal.ance | E233702 | - |
Appears in Collections: | D1. Contributo in Atti di convegno |
Files in This Item:
File | Description | Size | Format | |
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27. 2022 Bono Rossello - State estimation of pest populations subject to intermittend measurements.pdf | 389.71 kB | Adobe PDF | View/Open |
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