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This paper presents the application of a rough-set based neuro-fuzzy system (RNFS) in volatility forecasting by synergizing the information extraction of popular generalized auto-regressive conditional heteroscedasticity (GARCH) models with the human like interpretable RNFS. Additional intraday volatility indicators such as realized power variation (RPV) are proposed to further boost volatility forecasts...
Early-warning system of China's real estate is still in the development of a sound stage, and there are following two main aspects. Firstly, the selection of indicators is to be improved. Secondly, predictive capability of the turning point about the real estate business cycle is to be improved. Based on the above-mentioned problems, the Rough-GA-BP model proposed is applied to the real estate early-warning...
The less predictable characteristics of droughts make drought both a hazard and a disaster: a hazard because it is a natural accident of unpredictable occurrence but of recognisable recurrence, and a disaster because it causes the disruption of the water supply to the natural and agricultural ecosystems as well as to other human activities. What make less predictable characteristics of droughts is...
In this paper, a hybrid prediction model based on rough set (RS) and support vector machine (SVM), RSS prediction model, is proposed to explore the stock index futures tendency. In this approach, RS is used for feature vectors selection to reduce the computation complexity of SVM and then the SVM is used to identify stock index futures movement direction. To evaluate the prediction ability of RSS...
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