灰色神经网络组合模型在区域水质预测中的应用

Gray Neural Network Combination Model Applied in the Area Water Quality Forecasting

针对神经网络用于水质预测时需要大量数据才能获得较为准确的预测结果的局限性,为降低预测时对数据的依赖引入灰色模型,从而建立两者最优组合模型,以用于数据贫瘠时的情况。将该模型用于珠江支流的水质预测,结果表明,该模型拟合误差小,预测精度高。

Aiming at the deficiency of the neural network using in the water quality forecasting must need plentiful data. Adding the gray model was used to reducing the dependence on he data. Then constructing the combination of the two optimal model applied in the scarcity of the data. The model applied in the branch of the Pearl river, the result indicated that it can gain less error and exact forecast result.