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- W2374715945 abstract "In the multi-factor forecasting work,the forecasting objects and their influencing factors usually bear the non-linear relativity and have the characteristics of randomicity and non-linear movement,and at the same time the importance degree of each factor to the forecasting objects are not exactly the same,and also the capacity of study samples are small and information is insufficient.The multifactor foresting model which is the amalgamation of the grey wavelet neural network is established and applied to traffic forecast by making the best use of wavelet neural network which has the merit of strong nonlinear fitting to nonlinear function and the advantage of grey accumulated generating data weakening the randomicity of the original data and strengthening regularity.By contrasting with BP network,the result shows that this model is feasible and efficient,the accuracy of forecasting also increased." @default.
- W2374715945 created "2016-06-24" @default.
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- W2374715945 date "2010-01-01" @default.
- W2374715945 modified "2023-09-23" @default.
- W2374715945 title "Multi-factor Forecasting Model on the Integration of Grey Technology and Wavelet Network" @default.
- W2374715945 hasPublicationYear "2010" @default.
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