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With the boom of big data, the Internet contains more and more personal behavior information, but it is difficult to extract effectively. A model involving multivariate processing capability must be constructed to deal with these time series with complex characteristics. In this paper, a novel hybrid model embedding Baidu Search Index is therefore proposed to implement multi-step ahead subway passenger flow forecasting. Firstly, we collect data from informative Baidu Search Index, reduce dimensionality, and screen out the powerful predictors by statistical analysis. Secondly, we extract matching common modes at similar time scales between the subway passenger flow and screened Baidu Search Index via multivariate mode decomposition being optimized by multi-objective algorithm. Furthermore, to eliminate pseudo statistical causality, we select the optimal combination of modal components between subway passenger flow and its corresponding Baidu Search Index at each time scale by an innovative multi–modal analysis strategy. Thirdly, we reconstruct the forecasting values of each selected optimal combination as the final results. The empirical results of Beijing, Shanghai and Guangzhou show that the proposed model can significantly outperform six benchmark models in both the level and directional accuracy. So introducing Baidu Search Index creates a sound opportunity to enhance the subway passenger flow forecasting ability. [ABSTRACT FROM AUTHOR]

Abstract: External wall insulation plays an important role in building energy consumption through affecting cooling and heating energy uses. In this paper, a study on the effects of external wall insulation thickness on annual cooling and heating energy uses under different Chinese climates is reported. Firstly, two indexes: Energy Gain Ratio (EGR) and Relative Variation Ratio (RVR) of the sum of annual cooling and heating energy uses, to assess the effects of external wall insulation thickness on energy saving potential are introduced. Secondly, a model space having four different exterior zones facing four different orientations in an office building is presented and the settings of the model space described. Lastly, the simulated annual cooling and heating energy uses for the four different exterior zones at different external wall insulation thicknesses under three different climates in China, Guangzhou, Shanghai and Beijing, are reported. The results suggested that energy saving was significant by increasing the external wall insulation thickness in exterior zones facing all orientations under Beijing’s climate, since the heating energy use was dominant and can be reduced remarkably with the increase in insulation thickness. Under Shanghai’s climate, increasing external wall insulation thickness to over 26mm would not reduce the sum of annual heating and cooling energy uses in the south-facing exterior zone, but would help save energy in exterior zones facing the other three orientations. For all exterior zones under Guangzhou’s climate, it was, however, hardly possible to reduce the sum of annual heating and cooling energy uses by increasing the external wall insulation thickness. [Copyright &y& Elsevier]