Using DataMining to Predict Diseases in Vineyards and Olive Groves

Luís Alves, Rodrigo Rocha Silva, Jorge Bernardino

Abstract

Currently, the advancements in computer technology allows progress of the agricultural sector. Producers and service providers are exploring the value of information and its importance in increasing the productivity and profitability of a farm. This paper intends to evaluate various classification algorithms of data mining to predict various diseases in vineyards and olive groves. We propose using machine learning to predict diseases based on symptoms and weather data. The accuracy of classification algorithms like Random Forest, IBK, Naïve Bayes and SMO have been compared using Weka Software. Using our proposal, it is expected to reduce the incidence of diseases by more than 75%.

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Paper Citation


in Harvard Style

Alves L., Silva R. and Bernardino J. (2017). Using DataMining to Predict Diseases in Vineyards and Olive Groves.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 282-287. DOI: 10.5220/0006519002820287


in Bibtex Style

@conference{keod17,
author={Luís Alves and Rodrigo Rocha Silva and Jorge Bernardino},
title={Using DataMining to Predict Diseases in Vineyards and Olive Groves},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={282-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006519002820287},
isbn={978-989-758-272-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - Using DataMining to Predict Diseases in Vineyards and Olive Groves
SN - 978-989-758-272-1
AU - Alves L.
AU - Silva R.
AU - Bernardino J.
PY - 2017
SP - 282
EP - 287
DO - 10.5220/0006519002820287