Agricultural data prediction by means of neural network
| Autor: | Oldřich Trenz, V. Konečný, J. Šťastný |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
0106 biological sciences
Mathematical model Artificial neural network Computer science business.industry Simulation modeling Regression analysis 02 engineering and technology Machine learning computer.software_genre 01 natural sciences Agricultural and Biological Sciences (miscellaneous) Neural Network Simulation Set (abstract data type) Task (computing) Data prediction 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business General Economics Econometrics and Finance computer 010606 plant biology & botany |
| Zdroj: | ResearcherID |
| ISSN: | 1805-9295 0139-570X |
| Popis: | 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 a 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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