Application of Artificial Neural Networks for Yield Modeling of Winter Rapeseed Based on Combined Quantitative and Qualitative Data

Application of Artificial Neural Networks for Yield Modeling of Winter Rapeseed Based on Combined Quantitative and Qualitative Data

Rapeseed is considered as one of the most important oilseed crops in the world. Vegetable oil obtained from rapeseed is a valuable raw material for the food and energy industry as well as for industrial applications. Compared to other vegetable oils, it has a lower concentration of saturated fatty a...

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Bibliographic Details
Main Authors: Gniewko Niedbała, Magdalena Piekutowska, Jerzy Weres, Robert Korzeniewicz, Kamil Witaszek, Mariusz Adamski, Krzysztof Pilarski, Aneta Czechowska-Kosacka, Anna Krysztofiak-Kaniewska
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Agronomy
Subjects:
winter rapeseed
artificial neural networks
machine learning
yield prediction
yield simulation
mlp (multi-layer perceptron) network
sensitivity analysis
precision agriculture
sustainable agriculture
sustainability
Online Access:https://www.mdpi.com/2073-4395/9/12/781

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https://www.mdpi.com/2073-4395/9/12/781

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