Zur Kurzanzeige

Decision support system for agricultural management using prediction algorithm

dc.contributor.authorAnimas, Mark Ian
dc.contributor.authorByun, Yung-Cheol
dc.contributor.authorGerardo, Bobby D.
dc.contributor.authorConcepcion, Ma. Beth
dc.date.accessioned2024-08-12T09:16:20Z
dc.date.available2024-08-12T09:16:20Z
dc.date.issued2013-09-26
dc.identifier.citationAnimas, M. I., Byun, Y. C., Gerardo, B. D., & Concepcion, M. B. (2013, June). Decision support system for agricultural management using prediction algorithm. In 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS) (pp. 191-194). IEEE. https://doi.org/10.1109/ICIS.2013.6607839en
dc.identifier.isbn978-1-4799-0174-6
dc.identifier.urihttps://hdl.handle.net/20.500.14353/589
dc.description.abstractCurrently climate change is one of the major problems encountered due to the climatic controls interacting in various intensities and in different combinations. The proposed system includes mechanism that accepts/processes gathered data from Agricultural Research Center. The system uses Time Series Analysis; the collection of observations of well-defined data items obtained through repeated measurements over time which utilizes algorithm that is capable of formulating the trend. Upon prediction, the system displays table and graphs along with the recommended crops. The system had successfully determined the trend of rainfall and evaporation using prediction algorithm together with the recommended crops. It was able to display the result of prediction in graphical form and crop classification in tabular form.en
dc.description.sponsorshipThis would not have been possible without the guidance and the help of several individuals who, in one way or another, contributed of the study. Rachille A. Cenaroza, Margelyn P. Paches, and Ireas G. Talaue, members of the study, for the knowledge and support; And finally, the researchers’ academic home, The Institute of Information and Communications Technology for implanting in them the knowledge necessary for the completion of this research.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.subjectAgricultural managementen
dc.subjectPrediction Algorithmen
dc.subjectRainfall-Evaporation Predictionen
dc.subjectTrenden
dc.subject.lcshAgricultural industries--Managementen
dc.subject.lcshAgriculture--Researchen
dc.subject.lcshAlgorithmsen
dc.subject.lcshWeather forecastingen
dc.subject.lcshArtificial intelligenceen
dc.subject.lcshRain and rainfallen
dc.subject.lcshEvaporationen
dc.subject.lcshDecision support systems--Researchen
dc.subject.lcshFarm managementen
dc.titleDecision support system for agricultural management using prediction algorithmen
dc.typeConference paperen
dcterms.accessRightsLimited public accessen
dc.citation.firstpage191en
dc.citation.lastpage194en
dc.identifier.doihttps://doi.org/10.1109/ICIS.2013.6607839
dc.citation.conferencetitle2013 IEEE/ACIS 12th International Conference on Computer and Information Science, ICIS 2013 - Proceedingsen
local.isIndexedByISIen
local.isIndexedByScopusen
local.subject.agrovocalgorithmsen
local.subject.agrovocagricultureen
local.subject.agrovocweather forecastingen
local.subject.agrovocartificial intelligenceen
local.subject.agrovocdecision support systemsen
local.subject.agrovocrainen
dc.subject.sdgSDG 13 - Climate actionen


Dateien zu dieser Ressource

Thumbnail
Name:
PUB-CPR-L-2013-AnimasMI-FLT.pdf
Größe:
745.7Kb
Format:
PDF
Öffnen

Das Dokument erscheint in:

  • Conference Papers [14]
    Conference papers published externally, written by WVSU faculty members, staff, and students

Zur Kurzanzeige