Backpropagation neural networks with five data coding schemes were used to predict maize yield at three scales in east-central Indiana of the Midwest USA, using 1901-1996 local crop-stage weather data and yield data from farm, county, and state levels. Input data included precipitation and air tempe
✦ LIBER ✦
AE—Automation and Emerging Technologies: Prediction of Performance Indices and Optimal Parameters of Rough Rice Drying using Neural Networks
✍ Scribed by Qinghua Zhang; Simon X. Yang; Gauri S. Mittal; Shujuan Yi
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 199 KB
- Volume
- 83
- Category
- Article
- ISSN
- 1537-5110
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Arti"cial neural networks are gaining widespread acceptance in cereal grain classi"cation and identi"cation tasks. The choice of a neural network architecture and input features can pose a problem for a novice user. This research is aimed at evaluating the most commonly used neural network architect