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1. An artificial neural network model for estimating crop yields using remotely sensed information.

Author

Jiang, D., Yang, X., Clinton, N., and Wang, N.

Subjects
*CROP yields, *ARTIFICIAL neural networks, *REMOTE sensing, *MATHEMATICAL models, *BACK propagation, *ALGORITHMS
Abstract

Crop yield forecasting is a very important task for researchers in remote sensing. Problems exist with traditional statistical modelling (especially regression models) of nonlinear functions with multiple factors in the cropland ecosystem. This paper describes the successful application of an artificial neural network in developing a model for crop yield forecasting using back-propagation algorithms. The model has been adapted and calibrated using on the ground survey and statistical data, and it has proven to be stable and highly accurate. [ABSTRACT FROM AUTHOR]

Published
2004
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