Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about pos...Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.展开更多
In this article,mathematical modeling for the evaluation of reliability is studied using two methods.One of the methods,is developed based on possibility theory.The performance of the reliability of the system is of p...In this article,mathematical modeling for the evaluation of reliability is studied using two methods.One of the methods,is developed based on possibility theory.The performance of the reliability of the system is of prime concern.In view of this,the outcomes for the failure are required to evaluate with utmost care.In possibility theory,the reliability information data determined from decision-making experts are subjective.The samemethod is also related to the survival possibilities as against the survival probabilities.The other method is the one that is developed using the concept of approximation of closed interval including the piecewise quadratic fuzzy numbers.In this method,a decision-making expert is not sure of his/her estimates of the reliability parameters.Numerical experiments are performed to illustrate the efficiency of the suggested methods in this research.In the end,the paper is concluded with some future research directions to be explored for the proposed approach.展开更多
在物流供应商选择过程中,针对分布式评价语言环境下专家评价信息不完整问题,提出社会网络下考虑信息补全的群决策方法。考虑专家接受间接信任关系可能性的大小,提出一种新的信任传递模型来完善专家间的信任值;首次拓展Jensen-Shannon散...在物流供应商选择过程中,针对分布式评价语言环境下专家评价信息不完整问题,提出社会网络下考虑信息补全的群决策方法。考虑专家接受间接信任关系可能性的大小,提出一种新的信任传递模型来完善专家间的信任值;首次拓展Jensen-Shannon散度到分布式评价语言距离度量上,用于衡量专家之间的相似度;基于K-临近算法,设计改进的残缺评价信息补全方法;对专家信息进行集结并构建共识度量与反馈调节机制,得到群决策矩阵,并运用改进的EDAS(evaluation based on distance from average solution,离平均方案(平均解)距离)方法对方案进行排序;通过物流服务供应商综合评估算例验证该群决策方法的可行性和有效性。展开更多
目的探究最好自我(best possible self,BPS)训练对集训期新兵心理健康状况(乐观与悲观情绪、知觉压力和主观幸福感)的干预效果。方法采用非随机对照试验设计方案,以整群抽样法于2023年9月在某新兵训练基地抽取212名新兵,根据建制分为研...目的探究最好自我(best possible self,BPS)训练对集训期新兵心理健康状况(乐观与悲观情绪、知觉压力和主观幸福感)的干预效果。方法采用非随机对照试验设计方案,以整群抽样法于2023年9月在某新兵训练基地抽取212名新兵,根据建制分为研究组(100人,行BPS训练15 min/d)和对照组[112人,行日常生活(typical day,TD)表象训练,15 min/d],连续干预2周。于干预当天(T0),干预实施1周(T1)、2周(T2),干预结束后1周(T3)采用未来预期量表(Future Expectation Scale,FEX)、知觉压力量表(Chinese Perceived Stress Scale,CPSS)、正负性情绪量表(Positive and Negative Affect Scale,PANAS)和生活满意度量表(Satisfaction with Life Scale,SWLS)对2组被试进行测量,评估BPS训练对上述心理健康指标的训练效果。结果2组被试的人口统计学信息及各心理学基线指标均衡。随着训练的进行,2组在悲观情绪、知觉压力和主观幸福感(包含情感和认知幸福感)上的训练效果表现出明显的差异(P<0.05)。研究组T1~T3的悲观情绪相比基线(T0)明显降低(P<0.01),情感幸福感(P<0.01)和认知幸福感(P<0.01)明显升高,其知觉压力在T1(P<0.05)和T3(P<0.01)也明显降低;而对照组在训练前后却无上述明显变化。结论2周BPS训练可有效降低集训期新兵悲观情绪和知觉压力水平,提升其主观幸福感,促进新兵心理健康。展开更多
文摘Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.
文摘In this article,mathematical modeling for the evaluation of reliability is studied using two methods.One of the methods,is developed based on possibility theory.The performance of the reliability of the system is of prime concern.In view of this,the outcomes for the failure are required to evaluate with utmost care.In possibility theory,the reliability information data determined from decision-making experts are subjective.The samemethod is also related to the survival possibilities as against the survival probabilities.The other method is the one that is developed using the concept of approximation of closed interval including the piecewise quadratic fuzzy numbers.In this method,a decision-making expert is not sure of his/her estimates of the reliability parameters.Numerical experiments are performed to illustrate the efficiency of the suggested methods in this research.In the end,the paper is concluded with some future research directions to be explored for the proposed approach.
文摘在物流供应商选择过程中,针对分布式评价语言环境下专家评价信息不完整问题,提出社会网络下考虑信息补全的群决策方法。考虑专家接受间接信任关系可能性的大小,提出一种新的信任传递模型来完善专家间的信任值;首次拓展Jensen-Shannon散度到分布式评价语言距离度量上,用于衡量专家之间的相似度;基于K-临近算法,设计改进的残缺评价信息补全方法;对专家信息进行集结并构建共识度量与反馈调节机制,得到群决策矩阵,并运用改进的EDAS(evaluation based on distance from average solution,离平均方案(平均解)距离)方法对方案进行排序;通过物流服务供应商综合评估算例验证该群决策方法的可行性和有效性。
文摘目的探究最好自我(best possible self,BPS)训练对集训期新兵心理健康状况(乐观与悲观情绪、知觉压力和主观幸福感)的干预效果。方法采用非随机对照试验设计方案,以整群抽样法于2023年9月在某新兵训练基地抽取212名新兵,根据建制分为研究组(100人,行BPS训练15 min/d)和对照组[112人,行日常生活(typical day,TD)表象训练,15 min/d],连续干预2周。于干预当天(T0),干预实施1周(T1)、2周(T2),干预结束后1周(T3)采用未来预期量表(Future Expectation Scale,FEX)、知觉压力量表(Chinese Perceived Stress Scale,CPSS)、正负性情绪量表(Positive and Negative Affect Scale,PANAS)和生活满意度量表(Satisfaction with Life Scale,SWLS)对2组被试进行测量,评估BPS训练对上述心理健康指标的训练效果。结果2组被试的人口统计学信息及各心理学基线指标均衡。随着训练的进行,2组在悲观情绪、知觉压力和主观幸福感(包含情感和认知幸福感)上的训练效果表现出明显的差异(P<0.05)。研究组T1~T3的悲观情绪相比基线(T0)明显降低(P<0.01),情感幸福感(P<0.01)和认知幸福感(P<0.01)明显升高,其知觉压力在T1(P<0.05)和T3(P<0.01)也明显降低;而对照组在训练前后却无上述明显变化。结论2周BPS训练可有效降低集训期新兵悲观情绪和知觉压力水平,提升其主观幸福感,促进新兵心理健康。
