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Crop Yield Forecasting Using Artificial Neural Networks : A Comparison between Spatial and Temporal Models
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-23
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Our recent study using historic data of wheat yield and associated plantation area, rainfall, and temperature has shown that incorporating statistics and artificial neural networks can produce highly satisfactory forecasting of wheat yield.
However, no comparison has been made between the outcomes from the spatial neural network model and commonly used temporal neural network models in crop forecasting.
This paper presents the latest research outcomes from using both the spatial and temporal neural network models in crop forecasting.
Our simulation shows that the spatial NN model is able to predict the wheat yield with respect to a given plantation area with a high accuracy compared with the temporal NARNN and NARXNN models.
However, the high accuracy of the spatial NN model in crop yield forecasting is limited to the forecasting of crop yield only within normal ranges.
Users must be cautious when using either NARNN or NARXNN for crop yield forecasting due to their inconsistency between the results of training and forecasting.
American Psychological Association (APA)
Guo, William W.& Xue, Heru. 2014. Crop Yield Forecasting Using Artificial Neural Networks : A Comparison between Spatial and Temporal Models. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-503861
Modern Language Association (MLA)
Guo, William W.& Xue, Heru. Crop Yield Forecasting Using Artificial Neural Networks : A Comparison between Spatial and Temporal Models. Mathematical Problems in Engineering No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-503861
American Medical Association (AMA)
Guo, William W.& Xue, Heru. Crop Yield Forecasting Using Artificial Neural Networks : A Comparison between Spatial and Temporal Models. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-503861
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-503861