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  • 标题:Survey on Crop Prediction Using Back Propagation Neural
  • 本地全文:下载
  • 作者:Er. Lavina ; Er. Pankaj Dev Chadha
  • 期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
  • 印刷版ISSN:2277-6451
  • 电子版ISSN:2277-128X
  • 出版年度:2013
  • 卷号:3
  • 期号:7
  • 出版社:S.S. Mishra
  • 摘要:The aim of this research is to develop a farmer prediction system to identify crop suitable for particular soil. To achieve this Neural Network should be trained to perform correct prediction for farmers. After the network has been properly trained, it can be used to identify the crop suitable for particular type of soil. The Artificial neural networks are relatively crude electronic networks of "neurons" based on the neural structure of the brain. It process the records one at a time, and "learn" by comparing their prediction of the record with the known actual record. The errors from the initial prediction of the first record is fed back into the network, and used to modify the networks algorithm the second time around and so on for many iterations. An improved Back Propagation Neural Network model with improved learning algorithm provides an effective prediction tool for agriculture crops forecasting.
  • 关键词:Neural Network; Back Propagation; Learning algorithm; Training; Weights; Patterns
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