基于TOPSIS-模糊综合评判的模糊推理模型在开河预报中的应用

冰凌开封河受到较多自然和人为因素的影响,具有较高的不确定性,为了进一步提高冰凌开封河预测的精度,考虑各因素的综合作用成为解决问题的关键。先采用主成分分析法初步确定冰凌开封河历时影响因子的权重,运用模糊推理模型依据影响因子矩阵的相似性进行初步预测,进而采用TOPSIS-模糊综合评判模型对预报因子进行识别,筛选出合理的预报因子进行二次预测。运用实例对基于TOPSIS-模糊综合评判模型冰凌预报因子识别的模糊推理模型的效果进行了检验,同时与冰凌预报模糊优选神经网络BP模型进行对比,结果表明:在TOPSIS-模糊综合评判模型因子进行识别基础上的模糊推理模型预测精度较高、效果较好,既能够有效识别预报因子,又能够较好地提高预报封河、开河历时的精度,为凌汛预测提供了新的途径。

Application of the fuzzy reasoning model based on TOPSIS-fuzzy comprehensive evaluation to ice forecast

The break-up and freeze-up of the river is under the influence of various natural and human factors, and is an issue of great uncertainty. To further improve the accuracy of break-up and freeze-up forecasts, the key is to consider the combined action of various factors. First, we used the principal component analysis to preliminarily determine the weight of each factor that affects the break-up and freeze-up duration, and used the fuzzy reasoning model to conduct preliminary prediction according to the similarity of the impact factor matrix. Then we identified forecast factors using the TOPSIS-fuzzy comprehensive evaluation model and selected reasonable forecast factors to conduct secondary prediction. The fuzzy reasoning model based on TOPSIS-fuzzy comprehensive evaluation and ice forecast factor identification was tested in a case study and was compared with the fuzzy optimization neural network BP model. The results showed that the fuzzy reasoning model in this paper had high precision and good effects in prediction. It can effectively identify forecast factors, and can well improve the accuracy of freeze-up and break-up duration forecasts. It provides a new approach for ice run prediction.