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- W2384162039 abstract "Rough set integrated neural network method reflects the human's normal thinking mechanism which mixes the method of quantitative and qualitative, clear and uncertain, serial and parallel. This paper builds such a model which using rough set's 2 dimension reductive ability to reduce the noise and redundancy in the samples. So it improves the neural network's forecasting accuracy as well as reducing its' burden of learning. GA also is used in this paper to the attribute's discretion and neural network learning to find the optimized forecasting accuracy. Case study shows the hybrid model is more competitive than the similar neural network model." @default.
- W2384162039 created "2016-06-24" @default.
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- W2384162039 date "2002-01-01" @default.
- W2384162039 modified "2023-09-28" @default.
- W2384162039 title "A Hybrid Model of Forecasting in Finance Market" @default.
- W2384162039 hasPublicationYear "2002" @default.
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