为更加合理灵活地评估风光水多重不确定性给优化调度带来的风险性,基于分类机会约束提出了风光水出力高估/低估功率偏差置信风险量化计算方法,并计及多重不确定性置信风险构建经济/风险多目标优化调度模型。同时,充分利用智能电网可控资...为更加合理灵活地评估风光水多重不确定性给优化调度带来的风险性,基于分类机会约束提出了风光水出力高估/低估功率偏差置信风险量化计算方法,并计及多重不确定性置信风险构建经济/风险多目标优化调度模型。同时,充分利用智能电网可控资源,通过优化控制发电机出力、变压器变比和无功补偿容量等,实现在满足安全约束下系统运行成本最低和风险性最小的源网协调优化调度目标。为实现对所提复杂模型的高效求解,将高效优势可行解约束处理方法与具有动态资源分配策略的分解多目标进化算法相结合,提出了一种新型的多目标动态分解进化算法;并采用改进的逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)法自动提取最优折衷解以实现多目标优化调度决策。算例分析证明了所提方法的有效性和可行性。展开更多
Objective Coronary heart disease （CHD） is a multifactorial disease. This meta-analysis was performed to evaluate the relationship between angiotensinogen gene polymorphisms and CHD in the Chinese population. Methods...Objective Coronary heart disease （CHD） is a multifactorial disease. This meta-analysis was performed to evaluate the relationship between angiotensinogen gene polymorphisms and CHD in the Chinese population. Methods We searched literature in pubmed （1990- 2010.8） and CNKI （1990-2010.8） for all the relevant studies on 2 angiotensinogen polymorphisms （M235T and T174M） and risk of CHD. The meta-analysis software Stata 10.0 was used for ascertaining heterogeneity among individual studies and for combining all the studies. Furthermore,Egger＇s test and sensitivity analysis were performed to insure authenticity of the outcome.Results Ten associations studies on 2 angiotensinogen polymorphisms （M235T and T174M） were included in this meta-analysis. In a combined analysis, the summary per-allele odds ratio for CHD of the M235T polymorphism was 1.374 （95% confidence interval, 1.019 to 1.852） and T174M polymorphism was 4.089 （95% confidence interval, 1.697 to 9.851）. Conclusions The M235T polymorphism had weak but statistically significant association with CHD while the T174M polymorphism was more strongly associated with a CHD risk in Chinese population, but further confirmation studies are needed展开更多
文摘为更加合理灵活地评估风光水多重不确定性给优化调度带来的风险性,基于分类机会约束提出了风光水出力高估/低估功率偏差置信风险量化计算方法,并计及多重不确定性置信风险构建经济/风险多目标优化调度模型。同时,充分利用智能电网可控资源,通过优化控制发电机出力、变压器变比和无功补偿容量等,实现在满足安全约束下系统运行成本最低和风险性最小的源网协调优化调度目标。为实现对所提复杂模型的高效求解,将高效优势可行解约束处理方法与具有动态资源分配策略的分解多目标进化算法相结合,提出了一种新型的多目标动态分解进化算法;并采用改进的逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)法自动提取最优折衷解以实现多目标优化调度决策。算例分析证明了所提方法的有效性和可行性。
文摘Objective Coronary heart disease （CHD） is a multifactorial disease. This meta-analysis was performed to evaluate the relationship between angiotensinogen gene polymorphisms and CHD in the Chinese population. Methods We searched literature in pubmed （1990- 2010.8） and CNKI （1990-2010.8） for all the relevant studies on 2 angiotensinogen polymorphisms （M235T and T174M） and risk of CHD. The meta-analysis software Stata 10.0 was used for ascertaining heterogeneity among individual studies and for combining all the studies. Furthermore,Egger＇s test and sensitivity analysis were performed to insure authenticity of the outcome.Results Ten associations studies on 2 angiotensinogen polymorphisms （M235T and T174M） were included in this meta-analysis. In a combined analysis, the summary per-allele odds ratio for CHD of the M235T polymorphism was 1.374 （95% confidence interval, 1.019 to 1.852） and T174M polymorphism was 4.089 （95% confidence interval, 1.697 to 9.851）. Conclusions The M235T polymorphism had weak but statistically significant association with CHD while the T174M polymorphism was more strongly associated with a CHD risk in Chinese population, but further confirmation studies are needed
