Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coa...Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).展开更多
The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of sh...The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of shelterforest remediation planning and sustainable management. In this study, a protection efficiency index （PEI） model was established using the projection pursuit method to assess the protective quality of the coastal shelter forest at the coastal section scale of Dongshan Island, China. Three criteria were used, including forest stand structure, forest belt structure, and windbreak effect; each criterion further comprised multiple factors. Based on survey data of 31 plots in the coastal shelter forest of Dongshan Island, we calculated PEI values using a projection of a pursuit model. The result showed 64.5 % of the PEIs fell at or below the middle level, which can indicate the status of the coastal shelterbelt is unsatisfactory. To further explore whether the different bays and land use types create significant differences in PEIs and evaluation indices, we used an ANOVA to test the influence of various bays and forms of land use on coastal shelterbelts. The results showed that PEI and most of the indices differed significantly by bay; mean tree height, mean DBH, mean crown width, stand density, vegetation coverage, and wind velocity reduction differed significantly by land use. Therefore, relevant measures for different locations, bays and surrounding land use can be proposed to improve the existing conditions of the coastal shelterbelt. The results of this study provide a theoretical and technical framework for future changes and sustainable management of coastal shelterbelt on Dongshan Island.展开更多
基金provided by the Natural Science Foundation Project(Key)of Chongqing(No.cstc2013jjB0012)the National Natural Science Foundation of China(No.51434003)the National Natural Science Foundation of China(No.51474040)
文摘Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).
基金supported by the National Natural Science Foundation of China(Nos.31200365,31370624,and30870435)the Youth Science Fund of the Forestry College of Fujian Agriculture and Forestry University(No.6112C039V)
文摘The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of shelterforest remediation planning and sustainable management. In this study, a protection efficiency index （PEI） model was established using the projection pursuit method to assess the protective quality of the coastal shelter forest at the coastal section scale of Dongshan Island, China. Three criteria were used, including forest stand structure, forest belt structure, and windbreak effect; each criterion further comprised multiple factors. Based on survey data of 31 plots in the coastal shelter forest of Dongshan Island, we calculated PEI values using a projection of a pursuit model. The result showed 64.5 % of the PEIs fell at or below the middle level, which can indicate the status of the coastal shelterbelt is unsatisfactory. To further explore whether the different bays and land use types create significant differences in PEIs and evaluation indices, we used an ANOVA to test the influence of various bays and forms of land use on coastal shelterbelts. The results showed that PEI and most of the indices differed significantly by bay; mean tree height, mean DBH, mean crown width, stand density, vegetation coverage, and wind velocity reduction differed significantly by land use. Therefore, relevant measures for different locations, bays and surrounding land use can be proposed to improve the existing conditions of the coastal shelterbelt. The results of this study provide a theoretical and technical framework for future changes and sustainable management of coastal shelterbelt on Dongshan Island.
