The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientif...The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientific decision-making of education policies.Therefore,based on this view and through shaping reasonable education policy values,this research gives full play to the driving force of educational scientific research on education policies and designs effective education decision-making information content and running agenda,thus optimizing the weigh principle of education policy proposals,advocating risk assessment and practice of education decisions,constructing institutional rationality of educational scientific decision-making,and finally realizing the rationality and scientificity of education policy decision-making.展开更多
The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to ov...The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.展开更多
Design frequently involves making tradeoffs to obtain the“optimal”solution to a design problem,often using intuition or past experience as a guide.Since vegetated roofing is a relatively complex and comparatively ne...Design frequently involves making tradeoffs to obtain the“optimal”solution to a design problem,often using intuition or past experience as a guide.Since vegetated roofing is a relatively complex and comparatively new technology to many practitioners,a rational,explicit method to help organize and rank the tradeoffs made during the design process is needed.This research comprises the creation of a framework diagramming the decision process involved in the selection of vegetated roofi ng systems.Through literature review,case studies and interviews with experts,the available knowledge is captured and organized to determine the critical parameters affecting design decisions.Six important evaluative categories are identifi ed and parameters within these categories are addressed in the context of a decision support system for green roof designers.A summation of the total importance of the advantages represented by each alternative is used to determine the most feasible green roof system for a particular project.The framework is demonstrated and compared with green roof designers’decision-making processes and conclusions are drawn regarding its effectiveness.展开更多
The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science.Tremendous unstructured COVID-19 publications make it challenging for policymakers t...The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science.Tremendous unstructured COVID-19 publications make it challenging for policymakers to obtain relevant evidence.Knowledge graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently.Here,we introduce a novel framework that can ex-tract the COVID-19 public health evidence knowledge graph(CPHE-KG)from papers relating to a modelling study.We screen out a corpus of 3096 COVID-19 modelling study papers by performing a literature assessment process.We define a novel annotation schema to construct the COVID-19 modelling study-related IE dataset(CPHIE).We also propose a novel multi-tasks document-level information extraction model SS-DYGIE++based on the dataset.Leveraging the model on the new corpus,we construct CPHE-KG containing 60,967 entities and 51,140 rela-tions.Finally,we seek to apply our KG to support evidence querying and evidence mapping visualization.Our SS-DYGIE++(SpanBERT)model has achieved a F1 score of 0.77 and 0.55 respectively in document-level entity recognition and coreference resolution tasks.It has also shown high performance in the relation identification task.With evidence querying,our KG can present the dynamic transmissions of COVID-19 pandemic in different countries and regions.The evidence mapping of our KG can show the impacts of variable non-pharmacological interventions to COVID-19 pandemic.Analysis demonstrates the quality of our KG and shows that it has the potential to support COVID-19 policy making in public health.展开更多
基金This paper is funded by the youth project of education of the National Social Science Foundation“Research on the value foundation of educational policy from the perspective of political philosophy”(CAA150123).
文摘The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientific decision-making of education policies.Therefore,based on this view and through shaping reasonable education policy values,this research gives full play to the driving force of educational scientific research on education policies and designs effective education decision-making information content and running agenda,thus optimizing the weigh principle of education policy proposals,advocating risk assessment and practice of education decisions,constructing institutional rationality of educational scientific decision-making,and finally realizing the rationality and scientificity of education policy decision-making.
基金Supported by the National Natural Science Foundation of China(20676013,61240047)
文摘The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.
文摘Design frequently involves making tradeoffs to obtain the“optimal”solution to a design problem,often using intuition or past experience as a guide.Since vegetated roofing is a relatively complex and comparatively new technology to many practitioners,a rational,explicit method to help organize and rank the tradeoffs made during the design process is needed.This research comprises the creation of a framework diagramming the decision process involved in the selection of vegetated roofi ng systems.Through literature review,case studies and interviews with experts,the available knowledge is captured and organized to determine the critical parameters affecting design decisions.Six important evaluative categories are identifi ed and parameters within these categories are addressed in the context of a decision support system for green roof designers.A summation of the total importance of the advantages represented by each alternative is used to determine the most feasible green roof system for a particular project.The framework is demonstrated and compared with green roof designers’decision-making processes and conclusions are drawn regarding its effectiveness.
基金This work was supported in part by the National Natural Science Foundation of China(Grants No.72025404 and No.71621002)Bei-jing Natural Science Foundation(L192012)Beijing Nova Program(Z201100006820085).
文摘The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science.Tremendous unstructured COVID-19 publications make it challenging for policymakers to obtain relevant evidence.Knowledge graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently.Here,we introduce a novel framework that can ex-tract the COVID-19 public health evidence knowledge graph(CPHE-KG)from papers relating to a modelling study.We screen out a corpus of 3096 COVID-19 modelling study papers by performing a literature assessment process.We define a novel annotation schema to construct the COVID-19 modelling study-related IE dataset(CPHIE).We also propose a novel multi-tasks document-level information extraction model SS-DYGIE++based on the dataset.Leveraging the model on the new corpus,we construct CPHE-KG containing 60,967 entities and 51,140 rela-tions.Finally,we seek to apply our KG to support evidence querying and evidence mapping visualization.Our SS-DYGIE++(SpanBERT)model has achieved a F1 score of 0.77 and 0.55 respectively in document-level entity recognition and coreference resolution tasks.It has also shown high performance in the relation identification task.With evidence querying,our KG can present the dynamic transmissions of COVID-19 pandemic in different countries and regions.The evidence mapping of our KG can show the impacts of variable non-pharmacological interventions to COVID-19 pandemic.Analysis demonstrates the quality of our KG and shows that it has the potential to support COVID-19 policy making in public health.
