Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

A Methodology for More Sustainable Agriculture Through Early Crop Frost Forecasting

Authors
Jose M. Cadenas, M. Carmen Garrido, Raquel Martínez-España
Corresponding Author
Jose M. Cadenas
Available Online 30 August 2021.
DOI
https://doi.org/10.2991/asum.k.210827.027How to use a DOI?
Keywords
Sustainable agriculture, Condensed Nearest Neighbour, Lagged attributes, Imprecise information
Abstract

Climate change is causing abrupt changes in temperature, which adds to earlier flowering of crops and possible crop failure due to negative temperatures at night. Anti-frost techniques exist to save crops but they require natural and human resources which increase costs. Therefore the application of these techniques has to be as precise as possible. In order to facilitate the decision making process for the activate anti-frost techniques, e.g. sprinkler irrigation, the farmer needs an application that is freely available, simple to use and provides a quick and reliable prediction of the expected temperature in an immediate future. The application that provides this information must be available on readily available devices (e.g., a mobile phone). For the application to run on these devices it should have low requirements. For the design of this application, we propose a methodology that obtains small models, and provides it a fast and accuracy. The methodology includes the creation and use of colorreda decision model designed with an instance selection technique and including imprecise information and lagged attributes to respect the time series data and the nature of the information. A real case study is carried out to implement the proposed methodology using Nearest Neighbour technique both instance selection and classification. The results show reduced models with an high accuracy which allows us to create a lightweight model that can be easily updated in a mobile application.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - Jose M. Cadenas
AU  - M. Carmen Garrido
AU  - Raquel Martínez-España
PY  - 2021
DA  - 2021/08/30
TI  - A Methodology for More Sustainable Agriculture Through Early Crop Frost Forecasting
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 195
EP  - 202
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.027
DO  - https://doi.org/10.2991/asum.k.210827.027
ID  - Cadenas2021
ER  -