Support vector regression (SVR) method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study...Support vector regression (SVR) method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study presents four SVR models by selecting linear, radial basis, spline, and polynomial functions as kernels, respectively for the prediction of urban dust fall levels. The inputs of the models are identified as industrial coal consumption, population density, traffic flow coefficient, and shopping density coefficient. The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes. In addition, a number of scenario analyses reveal that the most suitable parameters (insensitive loss function e, the parameter to reduce the influence of error C, and discrete level or average distribution of parameters σ) are 0.001, 0.5, and 2 000, respectively.展开更多
DD (Dust deposition) was monitored over a 6-month period (April to September, 2011) at four sites located in villages near CADDⅡ(coal ash disposal site Divkovici Ⅱ), one inside recultivated CADDⅠ (coal ash d...DD (Dust deposition) was monitored over a 6-month period (April to September, 2011) at four sites located in villages near CADDⅡ(coal ash disposal site Divkovici Ⅱ), one inside recultivated CADDⅠ (coal ash disposal site Divkovici Ⅰ) and at one in the middle of forest barrier as control site. The main aim of this paper is to perform monitoring of air dust pollution in the area by measuring of dust deposition, different metals associated with it, and probable adverse effects on human health. Concentrations of metals were measured by using Perkin-Elmer model Inductively Coupled Plasma and statistically evaluated with SPSS 17.0 statistical program. There was a correlation between some metals (Mn, Mo and Pb) and DD distribution. The daily limit values for concentration of DD proposed by national "Regulations on air quality" (200 mg/m^2d average annual value and 350 mg/m^2d high value) exceed at three measuring sites. The average maximum content of DD was 684.8 mg/m^2d downwind of CADDII, and the average minimum was 46.8 mg/m^2d at measuring site F. Concentrations of pollutants hazardous to the environment as Ni, Cr, Cu, Mo, Mn and Pb vary from one site to another.展开更多
基金Projects(2007JT3018, 2008JT1013, 2009FJ4056) supported by the Key Project in Hunan Science and Technology Program, ChinaProject(20090161120014) supported by the New Teachers Sustentation Fund in Doctoral Program, Ministry of Education, China
文摘Support vector regression (SVR) method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study presents four SVR models by selecting linear, radial basis, spline, and polynomial functions as kernels, respectively for the prediction of urban dust fall levels. The inputs of the models are identified as industrial coal consumption, population density, traffic flow coefficient, and shopping density coefficient. The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes. In addition, a number of scenario analyses reveal that the most suitable parameters (insensitive loss function e, the parameter to reduce the influence of error C, and discrete level or average distribution of parameters σ) are 0.001, 0.5, and 2 000, respectively.
文摘DD (Dust deposition) was monitored over a 6-month period (April to September, 2011) at four sites located in villages near CADDⅡ(coal ash disposal site Divkovici Ⅱ), one inside recultivated CADDⅠ (coal ash disposal site Divkovici Ⅰ) and at one in the middle of forest barrier as control site. The main aim of this paper is to perform monitoring of air dust pollution in the area by measuring of dust deposition, different metals associated with it, and probable adverse effects on human health. Concentrations of metals were measured by using Perkin-Elmer model Inductively Coupled Plasma and statistically evaluated with SPSS 17.0 statistical program. There was a correlation between some metals (Mn, Mo and Pb) and DD distribution. The daily limit values for concentration of DD proposed by national "Regulations on air quality" (200 mg/m^2d average annual value and 350 mg/m^2d high value) exceed at three measuring sites. The average maximum content of DD was 684.8 mg/m^2d downwind of CADDII, and the average minimum was 46.8 mg/m^2d at measuring site F. Concentrations of pollutants hazardous to the environment as Ni, Cr, Cu, Mo, Mn and Pb vary from one site to another.