| 摘要: |
| 由于影响因素的复杂性，预测降水量具有相当的难度。在假区域长时间内降水量和蒸发量保持平衡的基础上，用BP人工神经网络建立了陕西省汉中市的降水量预测模型，根据前3个月降水量和蒸发量对降水量资料进行了模拟预测，结果认为其准确率为84％，合格率为100％。 |
| 关键词: 降水量 BP人工神经网络 预测模型 |
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| Application of BP artificial neural network model in forecast of quantity of precipitation |
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| Abstract: |
| Because of the complexity of influencial factors,it is very difficult to forecast the quantity of precipitation.Based on the quantity balance of evaporation and precipitation in a long time in a area,BP artificial neural network model was applied to build forecast model of quantity of precipitation.It is based on former three months’quantity of precipitation and evaporation to simulate and forecast this month’s quantity of precipitation.The result is analyzed and indicates that the ratio of nicety is 84% and the ratio of eligibility is 100%. |
| Key words: quantity of precipitation BP artificial neural network forecast model |
