最优化决策风格包含最优化目标和最优化策略两维度,两者表现出不同的适应功能。目前研究常依据总均分或单独的维度得分进行分析,这种方法未能充分揭示最优化决策者的复杂性。本文基于动机视角分析了最优化两维度的区别和联系,并由此提...最优化决策风格包含最优化目标和最优化策略两维度,两者表现出不同的适应功能。目前研究常依据总均分或单独的维度得分进行分析,这种方法未能充分揭示最优化决策者的复杂性。本文基于动机视角分析了最优化两维度的区别和联系,并由此提出以人为中心的最优化四象限理论模型。该模型将决策者区分为混合型、目标型、策略型和非最优化四种类型。依据该模型,本文从情绪适应和社会消费行为适应两个角度梳理和论述了不同类型最优化者的适应功能。最后本文讨论了最优化四象限模型的理论与实践价值,并建议将来应从最优化的维度交互、以人为中心视角、纵向分析、影响因素和神经基础等方面进一步探索,以深化对不同最优化类型适应功能的理解。The maximization decision-making style includes two dimensions: the maximization goal and the maximization strategy, each exhibiting distinct adaptive functions. Most studies often rely on scores of the overall or the specific dimension, a method that fails to fully capture the complexity of maximizers. This review analyzes the differences and connections between the two dimensions of maximization from the perspective of motivation, leading to the proposal of a person-centered maximization four-quadrant model. This model categorizes decision-makers into four types: mixed-type, goal-oriented, strategy-oriented, and non-maximizers. Based on this model, this review analyzes the adaptive functions of different types of maximizers from the perspectives of emotional adaptation and social consumption behavior adaptation. Finally, this review discusses the theoretical and practical value of the maximization four-quadrant model, and suggests that it should be further explored from the aspects of dimensional interaction of maximization, person-centered perspective, longitudinal analysis, influencing factors and neurological foundations, to enhance understanding of adaptive functions of different types of maximizers.展开更多
为了实现对氮化镓高电子迁移率晶体管GaN HEMT(gallium nitride high electron mobility transistor)高速开关带来的开通过压、误导通、开关振荡和EMI噪声等问题展开定量的仿真分析,提出了一种基于建模数据和最优化算法的门极增强型GaN ...为了实现对氮化镓高电子迁移率晶体管GaN HEMT(gallium nitride high electron mobility transistor)高速开关带来的开通过压、误导通、开关振荡和EMI噪声等问题展开定量的仿真分析,提出了一种基于建模数据和最优化算法的门极增强型GaN HEMT电热行为模型建模方法。相比较于常规GaN HEMT行为模型,所提出的建模方法采用2个简单的建模公式实现了对GaN HEMT在第一和第三象限宽工作温度范围内的电热特性进行准确的建模。同时采用一个紧凑的建模公式实现对GaN HEMT非线性寄生电容的精确建模。此外,提出了一种遗传算法和Levenberg-Marquardt算法组合的优化算法,基于该优化算法和建模数据实现了对建模参数的快速提取,在较大程度上减小了建模时间和工作量。仿真表明,所提出的建模方法能够实现对不同公司多个型号的GaN HEMT器件展开精确的建模。最后通过吻合的动态仿真和实验数据验证了所提建模方法的正确性和有效性。展开更多
文摘最优化决策风格包含最优化目标和最优化策略两维度,两者表现出不同的适应功能。目前研究常依据总均分或单独的维度得分进行分析,这种方法未能充分揭示最优化决策者的复杂性。本文基于动机视角分析了最优化两维度的区别和联系,并由此提出以人为中心的最优化四象限理论模型。该模型将决策者区分为混合型、目标型、策略型和非最优化四种类型。依据该模型,本文从情绪适应和社会消费行为适应两个角度梳理和论述了不同类型最优化者的适应功能。最后本文讨论了最优化四象限模型的理论与实践价值,并建议将来应从最优化的维度交互、以人为中心视角、纵向分析、影响因素和神经基础等方面进一步探索,以深化对不同最优化类型适应功能的理解。The maximization decision-making style includes two dimensions: the maximization goal and the maximization strategy, each exhibiting distinct adaptive functions. Most studies often rely on scores of the overall or the specific dimension, a method that fails to fully capture the complexity of maximizers. This review analyzes the differences and connections between the two dimensions of maximization from the perspective of motivation, leading to the proposal of a person-centered maximization four-quadrant model. This model categorizes decision-makers into four types: mixed-type, goal-oriented, strategy-oriented, and non-maximizers. Based on this model, this review analyzes the adaptive functions of different types of maximizers from the perspectives of emotional adaptation and social consumption behavior adaptation. Finally, this review discusses the theoretical and practical value of the maximization four-quadrant model, and suggests that it should be further explored from the aspects of dimensional interaction of maximization, person-centered perspective, longitudinal analysis, influencing factors and neurological foundations, to enhance understanding of adaptive functions of different types of maximizers.
