TELKOMNIKA Telecommunication, Computing, Electronics and Control
Predictions on wheat crop yielding through fuzzy set theory and optimization techniques
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Predictions on wheat crop yielding through fuzzy set theory and optimization techniques
Predictions on wheat crop yielding through fuzzy set theory and optimization techniques
Subject
Agriculture, Crops, Fuzzy set theory, Optimization techniques, Performance, Prediction, Wheat
Description
Agricultural field’s production is commonly measured through the
performance of the crops in terms of sow amount, climatology, and the type of crop, among other. Therefore, prediction on the performance of the crops can aid cultivators to make better informed decisions and help the agricultural field. This research work presents a prediction on wheat crop using the fuzzy set theory and the use of optimization techniques, in both; traditional methods and evolutionary meta-heuristics. The performance prediction in this research has its core on the following parameters: biomass, solar radiation, rainfall, and infield’s water extractions. Besides, the needed standards and the efficiency index (EFI) used come from already developed models; such standards include: the root-mean-square error (RMSE), the standard deviation, and the precision percentage. The application of a genetic algorithm on a Takagi-
Sugeno system requires and highly precise prediction on wheat cropping; being, 0.005216 the error estimation, and 99.928 the performance percentage.
performance of the crops in terms of sow amount, climatology, and the type of crop, among other. Therefore, prediction on the performance of the crops can aid cultivators to make better informed decisions and help the agricultural field. This research work presents a prediction on wheat crop using the fuzzy set theory and the use of optimization techniques, in both; traditional methods and evolutionary meta-heuristics. The performance prediction in this research has its core on the following parameters: biomass, solar radiation, rainfall, and infield’s water extractions. Besides, the needed standards and the efficiency index (EFI) used come from already developed models; such standards include: the root-mean-square error (RMSE), the standard deviation, and the precision percentage. The application of a genetic algorithm on a Takagi-
Sugeno system requires and highly precise prediction on wheat cropping; being, 0.005216 the error estimation, and 99.928 the performance percentage.
Creator
Julio Barón Velandia, Norbey Danilo Muñoz Cañón, Brayan Leonardo Sierra Forero
Source
DOI: 10.12928/TELKOMNIKA.v18i6.15870
Publisher
Universitas Ahmad Dahlan
Date
October 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Julio Barón Velandia, Norbey Danilo Muñoz Cañón, Brayan Leonardo Sierra Forero, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Predictions on wheat crop yielding through fuzzy set theory and optimization techniques,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/4166.
Predictions on wheat crop yielding through fuzzy set theory and optimization techniques,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/4166.