Regarding KMV model identification credit risk profile of small and medium-sized listed companies, at present, domestic scholars has made some achievements in the process of the KMV model combined with China’s nation...Regarding KMV model identification credit risk profile of small and medium-sized listed companies, at present, domestic scholars has made some achievements in the process of the KMV model combined with China’s national conditions. In this paper, we will amend the model by using uncertain interest rate instead of fixed rate on the basis of existing research. Comparing the uncertain KMV model to traditional KMV model with ST-listed companies and non-ST-listed companies in Shanghai and Shenzhen stock exchange, we find that it performs slightly better as a predictor in uncertain KMV model and in out of sample forecasts.展开更多
Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs...Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR,by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly,a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.展开更多
光伏出力的随机性和负荷用电的波动性对微电网的优化调度影响显著,为此提出了预测-调节-决策一体化的策略框架。基于高斯过程回归(Gaussian process regression,GPR)将光伏出力和负荷用电典型日历史数据自适应生成的置信区间与鲁棒优化...光伏出力的随机性和负荷用电的波动性对微电网的优化调度影响显著,为此提出了预测-调节-决策一体化的策略框架。基于高斯过程回归(Gaussian process regression,GPR)将光伏出力和负荷用电典型日历史数据自适应生成的置信区间与鲁棒优化中不确定集的构建相结合,建立了基于区间概率不确定集的自适应鲁棒优化调度模型。首先,通过GPR生成自适应鲁棒优化调度模型中不确定集的固定项,然后调节决策环节所考虑的风险水平以确定不确定集中的波动项,进而确定衡量不同调度保守度下的不确定集边界;接着采用预测区间质量评测指标来考核各个不确定集所对应的区间优劣。最后,通过改进的IEEE-37节点微电网系统验证了所提模型在有效抵御光伏出力和负荷用电波动的同时保持较低的运行成本。展开更多
文摘Regarding KMV model identification credit risk profile of small and medium-sized listed companies, at present, domestic scholars has made some achievements in the process of the KMV model combined with China’s national conditions. In this paper, we will amend the model by using uncertain interest rate instead of fixed rate on the basis of existing research. Comparing the uncertain KMV model to traditional KMV model with ST-listed companies and non-ST-listed companies in Shanghai and Shenzhen stock exchange, we find that it performs slightly better as a predictor in uncertain KMV model and in out of sample forecasts.
基金partly supported by the National Natural Science Foundation of China(71371053)the Social Science Foundation of Fujian Province(FJ2015C111)
文摘Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR,by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly,a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.
文摘光伏出力的随机性和负荷用电的波动性对微电网的优化调度影响显著,为此提出了预测-调节-决策一体化的策略框架。基于高斯过程回归(Gaussian process regression,GPR)将光伏出力和负荷用电典型日历史数据自适应生成的置信区间与鲁棒优化中不确定集的构建相结合,建立了基于区间概率不确定集的自适应鲁棒优化调度模型。首先,通过GPR生成自适应鲁棒优化调度模型中不确定集的固定项,然后调节决策环节所考虑的风险水平以确定不确定集中的波动项,进而确定衡量不同调度保守度下的不确定集边界;接着采用预测区间质量评测指标来考核各个不确定集所对应的区间优劣。最后,通过改进的IEEE-37节点微电网系统验证了所提模型在有效抵御光伏出力和负荷用电波动的同时保持较低的运行成本。
