We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area b...We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area between the minimum and maximum range of an input feature value into three equal parts. Then, we produced self-organizing product maps using classification data inputs. Finally, we applied our method to five product types and confirmed its effectiveness. In this paper, we propose a method for selecting alternatives from a product map, in which we have located a favorite several examples of selecting alternatives and making decisions using cluster, and/or from a favorite component map. We then show the AHP （Analytic Hierarchy Process）.展开更多
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
The task of selecting robotic mechanic assembly technologies (RMAT) is considered as a multi-criteria optimization task, which in this formulation is solved on the set of previously obtained solutions regarding the se...The task of selecting robotic mechanic assembly technologies (RMAT) is considered as a multi-criteria optimization task, which in this formulation is solved on the set of previously obtained solutions regarding the selection of RMAT. The purpose of the paper is to increase the efficiency of technological preparation of robotic mechanical assembly production of machine and instrument engineering due to a new approach to the selection of RMAT using Pareto optimization and the peculiarities of the selection task formulation. The novelty consists in the further development of a science-based approach to solving multi-criteria selection task, based on the first proposed formalisms of the specified process, which reflect the peculiarities of the selection task formulation, its meaningful essence and the content of the Pareto optimization method. The practical value of the research lies in the proposed engineering-acceptable approach to solving applied multi-criteria selection tasks on the example of RMAT selection, which is invariant to the statement of the selection task, the dimension of the task, and its meaningful essence. The methods of discrete optimization, fuzzy multi-criteria selection of alternatives, and the Pareto optimization method were used for the research. The main results of this work consist of the development of formalisms and the demonstration of the efficiency of the proposed approach for the applied task of RMAT selection. The peculiarity of the developed approach is the combination of Pareto optimization, performed on a discrete set of local criteria. Directions for further research are presented.展开更多
文摘We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area between the minimum and maximum range of an input feature value into three equal parts. Then, we produced self-organizing product maps using classification data inputs. Finally, we applied our method to five product types and confirmed its effectiveness. In this paper, we propose a method for selecting alternatives from a product map, in which we have located a favorite several examples of selecting alternatives and making decisions using cluster, and/or from a favorite component map. We then show the AHP （Analytic Hierarchy Process）.
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.
文摘The task of selecting robotic mechanic assembly technologies (RMAT) is considered as a multi-criteria optimization task, which in this formulation is solved on the set of previously obtained solutions regarding the selection of RMAT. The purpose of the paper is to increase the efficiency of technological preparation of robotic mechanical assembly production of machine and instrument engineering due to a new approach to the selection of RMAT using Pareto optimization and the peculiarities of the selection task formulation. The novelty consists in the further development of a science-based approach to solving multi-criteria selection task, based on the first proposed formalisms of the specified process, which reflect the peculiarities of the selection task formulation, its meaningful essence and the content of the Pareto optimization method. The practical value of the research lies in the proposed engineering-acceptable approach to solving applied multi-criteria selection tasks on the example of RMAT selection, which is invariant to the statement of the selection task, the dimension of the task, and its meaningful essence. The methods of discrete optimization, fuzzy multi-criteria selection of alternatives, and the Pareto optimization method were used for the research. The main results of this work consist of the development of formalisms and the demonstration of the efficiency of the proposed approach for the applied task of RMAT selection. The peculiarity of the developed approach is the combination of Pareto optimization, performed on a discrete set of local criteria. Directions for further research are presented.
