Agricultural data prediction by means of neural network

Jiří Šťastný, Vladimír Konečný and Oldřich Trenz
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Jiří Šťastný: Department of Computer Science, Faculty of Business and Economics, Mendel University in Brno, Brno, Czech Republic
Vladimír Konečný: Department of Computer Science, Faculty of Business and Economics, Mendel University in Brno, Brno, Czech Republic
Oldřich Trenz: Department of Computer Science, Faculty of Business and Economics, Mendel University in Brno, Brno, Czech Republic

Agricultural Economics, 2011, vol. 57, issue 7, 356-361

Abstract: The contribution deals with the prediction of crop yield levels, using an artificial intelligence approach, namely a multi-layer neural network model. Subsequently, we are contrasting this approach with several non-linear regression models, the usefulness of which has been tested and published several times in the specialized periodicals. The main stress is placed on judging the accuracy of the individual methods and of the implementation. A neural network simulation device is that which enables the user to set an adequate configuration of the neural network vis á vis the required task. The conclusions can be generalized for other tasks of a similar nature, especially for the tasks of a non-linear character, where the benefits of this method increase.

Keywords: neural network; multi-layer perceptron; approximation; learning; regression (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:57:y:2011:i:7:id:108-2011-agricecon

DOI: 10.17221/108/2011-AGRICECON

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