Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooper...Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.展开更多
The technological scheme of a hard rock surface mine is a multiple level production system of interdependently func-tioning elements. Selection of the optimum combination of its elements constitutes a complex multiple...The technological scheme of a hard rock surface mine is a multiple level production system of interdependently func-tioning elements. Selection of the optimum combination of its elements constitutes a complex multiple variant and criteria problem of decision making. In this paper describes the theoretical part of the method proposed for the quantitative analysis and selection of the most competent technological schemes, based on the mathematical formulations of the selection criteria of the element of each level as functions of the alternative variants of the elements of the level and its adjacent levels. It is realized in accordance to standard procedures of decision making in the formation of the economical mathematical model of the cumulative influence of levels and elements on the effectiveness of all alternative variants in their analysis and generation of a small subset of the most competent variants, which are subjected to further analysis using the criterion of reliability in the generation of the optimum technological scheme. The scientific challenge inherent in its realization constitutes a PhD research opportunity for those interested in the problems of optimization in hard rock surface mines.展开更多
The research work on thermophysical properties of difluoromethane (HFC-32) is summarized. Experimental data of critical parameters, vapor pressure, PVT, speed of sound, ideal-gas heat capacity, surface tension, viscos...The research work on thermophysical properties of difluoromethane (HFC-32) is summarized. Experimental data of critical parameters, vapor pressure, PVT, speed of sound, ideal-gas heat capacity, surface tension, viscosity, thermal conductivity are given and corresponding correlations are developed. The cross equation of state, the correlations of saturated liquid density and second virial coefficient for HFC-32 are also developed.展开更多
Probabilistic load forecasting(PLF)is able to present the uncertainty information of the future loads.It is the basis of stochastic power system planning and operation.Recent works on PLF mainly focus on how to develo...Probabilistic load forecasting(PLF)is able to present the uncertainty information of the future loads.It is the basis of stochastic power system planning and operation.Recent works on PLF mainly focus on how to develop and combine forecasting models,while the feature selection issue has not been thoroughly investigated for PLF.This paper fills the gap by proposing a feature selection method for PLF via sparse L1-norm penalized quantile regression.It can be viewed as an extension from point forecasting-based feature selection to probabilistic forecasting-based feature selection.Since both the number of training samples and the number of features to be selected are very large,the feature selection process is casted as a large-scale convex optimization problem.The alternating direction method of multipliers is applied to solve the problem in an efficient manner.We conduct case studies on the open datasets of ten areas.Numerical results show that the proposed feature selection method can improve the performance of the probabilistic forecasting and outperforms traditional least absolute shrinkage and selection operator method.展开更多
In this paper, a new ternary non-azeotropic mixture of HFC-161/125/143a (0.15/0.45/0.40 in mass fraction), as a promising mixed refrigerant to R404A, is presented. The ozone depletion potential (ODP) of the new refrig...In this paper, a new ternary non-azeotropic mixture of HFC-161/125/143a (0.15/0.45/0.40 in mass fraction), as a promising mixed refrigerant to R404A, is presented. The ozone depletion potential (ODP) of the new refrigerant is zero and its basic thermodynamic properties are similar to those of R404A, but its global warming potential (GWP) is much smaller than those of R507A and R404A. Meanwhile, theoretical calculations show that, under the working condition I (the average evaporation temperature: ?23 °C, the average condensing temperature: 43 °C, the superheat temperature: 28 °C, the subcooling temperature: 5 °C), the volumetric refrigerating effect and specific refrigerating effect of the new mixture are 2.33% and 15.48% higher, respectively, than those of R404A. The coefficient of performance (COP) of the new mixture is 5.19% higher than that of R404A and the pressure ratio of the new mixture is 0.82% lower than that of R404A. Equally, under the working condition II (the average evaporation temperature: ?40 °C, the average condensing temperature: 35 °C, the superheating temperature: 30 °C, the subcooling temperature: 5 °C), the volumetric refrigerating effect and specific refrigerating effect of the new mixture are 2.24% and 20.58% higher, respectively, than those of R404A. The COP of the new mixture is 4.60% higher than that of R404A and the pressure ratio of the new mixture is similar to that of R404A. The performances of the new mixture and R404A are compared in a vapor compressor refrigeration apparatus originally designed for R404A under several working conditions (condensing temperatures: 35–45 °C, evaporation temperatures: -40–-20 °C). Experimental results show that the new mixture can obtain a higher COP, by 6.3% to 12.1%, and a lower pressure ratio, by 1.8% to 6.6%, compared to R404A; although the discharge temperature of the new mixture is slightly higher than that of R404A. The advantages of the new mixture will be further verified in the actual system.展开更多
As part of the study on thermophysical properties of HFC-134a,this paper concerns itself with vapor pressure of HFC-134a in the temperature range of 279.15K to 365.15K,A total of 43 measurement data were measured duri...As part of the study on thermophysical properties of HFC-134a,this paper concerns itself with vapor pressure of HFC-134a in the temperature range of 279.15K to 365.15K,A total of 43 measurement data were measured during the experiment which was conducted on a high precision pVTx test apparatus designed by the authors with slight modifications,Uncertainties of temperature was ±10mK and of pressure was±500Pa,purity of sample was either 99.95wt%,or 99.98wt%,Data resulting from this experiment matched closely with the newest data published internationalyy,Compared to our porposed equation for calculating vapor pressure of HFC-134a,the RMS deviation cfexperimental data was only 0.0531%,showing relatively high precision.展开更多
基金supported by the National Natural Science Foundation of China (Nos.71771156,71971145,72171158).
文摘Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.
文摘The technological scheme of a hard rock surface mine is a multiple level production system of interdependently func-tioning elements. Selection of the optimum combination of its elements constitutes a complex multiple variant and criteria problem of decision making. In this paper describes the theoretical part of the method proposed for the quantitative analysis and selection of the most competent technological schemes, based on the mathematical formulations of the selection criteria of the element of each level as functions of the alternative variants of the elements of the level and its adjacent levels. It is realized in accordance to standard procedures of decision making in the formation of the economical mathematical model of the cumulative influence of levels and elements on the effectiveness of all alternative variants in their analysis and generation of a small subset of the most competent variants, which are subjected to further analysis using the criterion of reliability in the generation of the optimum technological scheme. The scientific challenge inherent in its realization constitutes a PhD research opportunity for those interested in the problems of optimization in hard rock surface mines.
文摘The research work on thermophysical properties of difluoromethane (HFC-32) is summarized. Experimental data of critical parameters, vapor pressure, PVT, speed of sound, ideal-gas heat capacity, surface tension, viscosity, thermal conductivity are given and corresponding correlations are developed. The cross equation of state, the correlations of saturated liquid density and second virial coefficient for HFC-32 are also developed.
基金supported by National Key R&D Program of China(No.2016YFB0900100).
文摘Probabilistic load forecasting(PLF)is able to present the uncertainty information of the future loads.It is the basis of stochastic power system planning and operation.Recent works on PLF mainly focus on how to develop and combine forecasting models,while the feature selection issue has not been thoroughly investigated for PLF.This paper fills the gap by proposing a feature selection method for PLF via sparse L1-norm penalized quantile regression.It can be viewed as an extension from point forecasting-based feature selection to probabilistic forecasting-based feature selection.Since both the number of training samples and the number of features to be selected are very large,the feature selection process is casted as a large-scale convex optimization problem.The alternating direction method of multipliers is applied to solve the problem in an efficient manner.We conduct case studies on the open datasets of ten areas.Numerical results show that the proposed feature selection method can improve the performance of the probabilistic forecasting and outperforms traditional least absolute shrinkage and selection operator method.
基金supported by the Nation Natural Science Foundation of China (No. 50806063)the Program for Key Innovative Research Team of Zhejiang Province (No. 2009R50036), China
文摘In this paper, a new ternary non-azeotropic mixture of HFC-161/125/143a (0.15/0.45/0.40 in mass fraction), as a promising mixed refrigerant to R404A, is presented. The ozone depletion potential (ODP) of the new refrigerant is zero and its basic thermodynamic properties are similar to those of R404A, but its global warming potential (GWP) is much smaller than those of R507A and R404A. Meanwhile, theoretical calculations show that, under the working condition I (the average evaporation temperature: ?23 °C, the average condensing temperature: 43 °C, the superheat temperature: 28 °C, the subcooling temperature: 5 °C), the volumetric refrigerating effect and specific refrigerating effect of the new mixture are 2.33% and 15.48% higher, respectively, than those of R404A. The coefficient of performance (COP) of the new mixture is 5.19% higher than that of R404A and the pressure ratio of the new mixture is 0.82% lower than that of R404A. Equally, under the working condition II (the average evaporation temperature: ?40 °C, the average condensing temperature: 35 °C, the superheating temperature: 30 °C, the subcooling temperature: 5 °C), the volumetric refrigerating effect and specific refrigerating effect of the new mixture are 2.24% and 20.58% higher, respectively, than those of R404A. The COP of the new mixture is 4.60% higher than that of R404A and the pressure ratio of the new mixture is similar to that of R404A. The performances of the new mixture and R404A are compared in a vapor compressor refrigeration apparatus originally designed for R404A under several working conditions (condensing temperatures: 35–45 °C, evaporation temperatures: -40–-20 °C). Experimental results show that the new mixture can obtain a higher COP, by 6.3% to 12.1%, and a lower pressure ratio, by 1.8% to 6.6%, compared to R404A; although the discharge temperature of the new mixture is slightly higher than that of R404A. The advantages of the new mixture will be further verified in the actual system.
文摘As part of the study on thermophysical properties of HFC-134a,this paper concerns itself with vapor pressure of HFC-134a in the temperature range of 279.15K to 365.15K,A total of 43 measurement data were measured during the experiment which was conducted on a high precision pVTx test apparatus designed by the authors with slight modifications,Uncertainties of temperature was ±10mK and of pressure was±500Pa,purity of sample was either 99.95wt%,or 99.98wt%,Data resulting from this experiment matched closely with the newest data published internationalyy,Compared to our porposed equation for calculating vapor pressure of HFC-134a,the RMS deviation cfexperimental data was only 0.0531%,showing relatively high precision.
