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