BP网络并行预测地下水位研究
Study of parallel prediction of groundwater table by BP neural network
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摘要: 提出了适用于孔隙承压水水源地的BP-遗传元胞自动机方法,这种方法的原理来源于地理元胞自动机的方法框架。把每个水源地作为一个元胞,每个水源地的下一时刻的状态由其本身、周围水源地上一时刻的状态和下一时刻的行为及它们所处的环境条件决定。并用该方法进行了多水源地水位并行预测,效果良好。Abstract: This paper proposes a suitable method of prediction of water table of water source field in confined aquifers in porous rocks. This prediction and optimization are done by BP-Genetic Geography cellular automata. The principle of this method is from the framework of geography cellular automata. Every field of water source is regarded as a cell. Scenario of next time of every field of water source is depended on the water source field itself and scenario of last time of the water source in the borderland and behavior of next time of water source in the borderland, as well as environmental conditions in the water source site.