A grey multi-stage decision making method is proposed for a type of grey multi-index decision problems with weighted values completely unknown and attributes as interval grey numbers. Firstly, a method for compar- ing...A grey multi-stage decision making method is proposed for a type of grey multi-index decision problems with weighted values completely unknown and attributes as interval grey numbers. Firstly, a method for compar- ing two grey numbers based on probability is developed to calculate weighted values of the attributes. Secondly, the experts＇ evaluation scores for attribute values are presented in terms of internal grey numbers. Finally, a weight solving method for multiple-stages evaluation is proposed. An example analysis verifies the availability of the proposed method. The method provides a new way of thinking for solving grey decision problem.展开更多
Restoring degraded forests and agricultural lands has become a global conservation priority. A growing number of tools can quantify ecosystem service tradeoffs associated with forest restoration. This evolving ＂tools...Restoring degraded forests and agricultural lands has become a global conservation priority. A growing number of tools can quantify ecosystem service tradeoffs associated with forest restoration. This evolving ＂tools landscape＂ presents a dilemma： more tools are available, but selecting appropriate tools has become more challenging. We present a Restoration Ecosystem Service Tool Selector （RESTS） framework that describes key characteristics of 13 ecosystem service assessment tools. Analysts enter information about their decision context, services to be analyzed, and desired outputs. Tools are filtered and presented based on five evaluative criteria： scalability, cost, time requirements, handling of uncertainty, and applicability to benefit-cost analysis. RESTS uses a spreadsheet interface but a web-based interface is planned. Given the rapid evolution of ecosystem services science, RESTS provides an adaptable framework to guide forest restoration decision makers toward tools that can help quantify ecosystem services in support of restoration.展开更多
From the mathematical point of view,the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation.The purpose is to activel...From the mathematical point of view,the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation.The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information,and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity.At the same time,the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand.The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity.Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model,the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios.The correlation analysis between the capacity limit level and the return under the optimal Bookinglimit decision,and the above two flexibility parameters are obtained.展开更多
In the paper, the determinate atlecation decision model and the probabilistic allocation decision model of a kind of renewable resource are separatly studied by means of dynamic programming, and the optimal allocation...In the paper, the determinate atlecation decision model and the probabilistic allocation decision model of a kind of renewable resource are separatly studied by means of dynamic programming, and the optimal allocation policy is given under some special conditions.展开更多
Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, t...Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.展开更多
Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily appli...Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.展开更多
Background:The vital signs of trauma patients are complex and changeable,and the prediction of blood transfusion demand mainly depends on doctors'experience and trauma scoring system;therefore,it cannot be accurat...Background:The vital signs of trauma patients are complex and changeable,and the prediction of blood transfusion demand mainly depends on doctors'experience and trauma scoring system;therefore,it cannot be accurately predicted.In this study,a machine learning decision tree algorithm[classification and regression tree(CRT)and eXtreme gradient boosting(XGBoost)]was proposed for the demand prediction of traumatic blood transfusion to provide technical support for doctors.Methods:A total of 1371 trauma patients who were diverted to the Emergency Department of the First Medical Center of Chinese PLA General Hospital from January 2014 to January 2018 were collected from an emergency trauma database.The vital signs,laboratory examination parameters and blood transfusion volume were used as variables,and the non-invasive parameters and all(non-invasive+invasive)parameters were used to construct an intelligent prediction model for red blood cell(RBC)demand by logistic regression(LR),CRT and XGBoost.The prediction accuracy of the model was compared with the area under curve(AUC).Results:For non-invasive parameters,the LR method was the best,with an AUC of 0.72[95%confidence interval(CI)0.657–0.775],which was higher than the CRT(AUC 0.69,95%CI 0.633–0.751)and the XGBoost(AUC 0.71,95%CI 0.654–0.756)(P<0.05).The trauma location and shock index are important prediction parameters.For all the prediction parameters,XGBoost was the best,with an AUC of 0.94(95%CI 0.893–0.981),which was higher than the LR(AUC 0.80,95%CI 0.744–0.850)and the CRT(AUC 0.82,95%CI 0.779–0.853)(P<0.05).Haematocrit(Hct)is an important prediction parameter.Conclusions:The classification performance of the intelligent prediction model of red blood cell transfusion in trauma patients constructed by the decision tree algorithm is not inferior to that of the traditional LR method.It can be used as a technical support to assist doctors to make rapid and accurate blood transfusion decisions in emergency rescue environment,so as to improve the success rate of patient treatment.展开更多
从功能性、安全性和经济性角度出发,构建漂浮式海上风电基础结构方案的多准则评价体系,确定评价指标。基于熵权-TOPSIS(technique for order preference by similarity to an ideal solution)法建立漂浮式海上风电基础结构方案多准则评...从功能性、安全性和经济性角度出发,构建漂浮式海上风电基础结构方案的多准则评价体系,确定评价指标。基于熵权-TOPSIS(technique for order preference by similarity to an ideal solution)法建立漂浮式海上风电基础结构方案多准则评价模型。通过案例分析,证明该评价模型可从客观角度进行漂浮式海上风电基础结构方案的评价,基于评价模型提出的优化方案具有合理性,能达到改善方案综合表现的效果。展开更多
基金Supported by the National Natural Science Foundation of China(90924022,70901041,71071077,71171113,71171116)the China Postdoctoral Science Foundation Funded Project(20100481137)+5 种基金the Humanisticand Social Science Foundation of the Ministry of Education of China(11YJC630032,12YJA630122,11YJC630273,09YJC630129)the Social Science Foundation of the College of Jiangsu Province(2011SJB630004)the Research Project of National Bureau of Statistics(2011LY008)the Jiangsu Planned Projects for Postdoctoral Research Funds(1101094C)the Qing Lan Project of Jiangsu Province(2010)the Educational Science Planning Key Projects of Jiangsu Piovince(B-a/2011/01/008)~~
文摘A grey multi-stage decision making method is proposed for a type of grey multi-index decision problems with weighted values completely unknown and attributes as interval grey numbers. Firstly, a method for compar- ing two grey numbers based on probability is developed to calculate weighted values of the attributes. Secondly, the experts＇ evaluation scores for attribute values are presented in terms of internal grey numbers. Finally, a weight solving method for multiple-stages evaluation is proposed. An example analysis verifies the availability of the proposed method. The method provides a new way of thinking for solving grey decision problem.
文摘Restoring degraded forests and agricultural lands has become a global conservation priority. A growing number of tools can quantify ecosystem service tradeoffs associated with forest restoration. This evolving ＂tools landscape＂ presents a dilemma： more tools are available, but selecting appropriate tools has become more challenging. We present a Restoration Ecosystem Service Tool Selector （RESTS） framework that describes key characteristics of 13 ecosystem service assessment tools. Analysts enter information about their decision context, services to be analyzed, and desired outputs. Tools are filtered and presented based on five evaluative criteria： scalability, cost, time requirements, handling of uncertainty, and applicability to benefit-cost analysis. RESTS uses a spreadsheet interface but a web-based interface is planned. Given the rapid evolution of ecosystem services science, RESTS provides an adaptable framework to guide forest restoration decision makers toward tools that can help quantify ecosystem services in support of restoration.
文摘From the mathematical point of view,the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation.The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information,and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity.At the same time,the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand.The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity.Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model,the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios.The correlation analysis between the capacity limit level and the return under the optimal Bookinglimit decision,and the above two flexibility parameters are obtained.
文摘In the paper, the determinate atlecation decision model and the probabilistic allocation decision model of a kind of renewable resource are separatly studied by means of dynamic programming, and the optimal allocation policy is given under some special conditions.
文摘Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.
文摘Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.
基金supported by the Key Project-subtopic of thea13th FiveYear PlanoMilitary Logistics Service Research of China (BWS16J006)。
文摘Background:The vital signs of trauma patients are complex and changeable,and the prediction of blood transfusion demand mainly depends on doctors'experience and trauma scoring system;therefore,it cannot be accurately predicted.In this study,a machine learning decision tree algorithm[classification and regression tree(CRT)and eXtreme gradient boosting(XGBoost)]was proposed for the demand prediction of traumatic blood transfusion to provide technical support for doctors.Methods:A total of 1371 trauma patients who were diverted to the Emergency Department of the First Medical Center of Chinese PLA General Hospital from January 2014 to January 2018 were collected from an emergency trauma database.The vital signs,laboratory examination parameters and blood transfusion volume were used as variables,and the non-invasive parameters and all(non-invasive+invasive)parameters were used to construct an intelligent prediction model for red blood cell(RBC)demand by logistic regression(LR),CRT and XGBoost.The prediction accuracy of the model was compared with the area under curve(AUC).Results:For non-invasive parameters,the LR method was the best,with an AUC of 0.72[95%confidence interval(CI)0.657–0.775],which was higher than the CRT(AUC 0.69,95%CI 0.633–0.751)and the XGBoost(AUC 0.71,95%CI 0.654–0.756)(P<0.05).The trauma location and shock index are important prediction parameters.For all the prediction parameters,XGBoost was the best,with an AUC of 0.94(95%CI 0.893–0.981),which was higher than the LR(AUC 0.80,95%CI 0.744–0.850)and the CRT(AUC 0.82,95%CI 0.779–0.853)(P<0.05).Haematocrit(Hct)is an important prediction parameter.Conclusions:The classification performance of the intelligent prediction model of red blood cell transfusion in trauma patients constructed by the decision tree algorithm is not inferior to that of the traditional LR method.It can be used as a technical support to assist doctors to make rapid and accurate blood transfusion decisions in emergency rescue environment,so as to improve the success rate of patient treatment.
文摘从功能性、安全性和经济性角度出发,构建漂浮式海上风电基础结构方案的多准则评价体系,确定评价指标。基于熵权-TOPSIS(technique for order preference by similarity to an ideal solution)法建立漂浮式海上风电基础结构方案多准则评价模型。通过案例分析,证明该评价模型可从客观角度进行漂浮式海上风电基础结构方案的评价,基于评价模型提出的优化方案具有合理性,能达到改善方案综合表现的效果。
