Agricultural data prediction by means of neural network
O. Trenz, J. Šťastný, V. Konečnýhttps://doi.org/10.17221/108/2011-AGRICECONCitation:Trenz O., Šťastný J., Konečný V. (2011): Agricultural data prediction by means of neural network. Agric. Econ. – Czech, 57: 356-361.
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