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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 energy of coal as the basis for rapid economic development plays a supporting role. In the past, the accuracy of forecasting coal demand is not very satisfactory. In this paper, rough set for the coal demand factors affecting the reduction, the core factors extracted using BP neural network to predict, through the results of China coal demand forecast can be seen that the value of history fit...
An intelligent method on short-term prediction on water bloom of BP neural network based on rough set and wavelet analysis is proposed in this paper. This method analyzes factors of effecting the outbreak of water bloom, and these many factors which were processed by reduction method based on rough set were used as input information of the prediction model; after analyzing the main input information...
The paper gives a BP neural network (BPNN) prediction model of the ambient air quality based on rough set theory. We make first the reduction of monitoring data of the pollution sources using the theory of rough set, extract the tidy rules. Then the topological structure of the multilayer BPNN and the nerve cells of the connotative layer are defined with these rules. After that the connected weight...
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