| 摘要: |
| 利用混沌理论，对湖北省某地区小麦条锈病受灾率进行混沌特征验证，然后利用BP神经网络非线性逼近器能力,建立预测模型，利用重构相空间，确定神经网络的输入节点数及输入值，并引入遗传算法优化BP神经网络参数，对受灾率进行了成功预报。 |
| 关键词: 小麦受灾率预报 混沌特征 重构相空间 GA-BPNN模型 |
| DOI： |
| 分类号:TP391.41 |
| 基金项目:湖北省教育厅科研项目（2001D69001） |
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| Research on chaotic characteristics of the disaster rate of crops and its GA-BPNN forecasting model |
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ZHANG Jing
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| Abstract: |
| The chaos theory is used to test chaotic characteristics of the disaster rate of wheat rust certain part of Hubei province.Then the forecasting model is established to forecast the disaster rate by combining BP-NN with GA.With reconstruction of phase space,determining the input numbers and values and the optimized BP algorithms,the disaster rate has been successfully forecasted. |
| Key words: wheat disaster rate forecast chaos character reconstruction of phase space GA-BPNN model |
