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相关概念视频

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Decision Making01:20

Decision Making

109
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
109
Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Framing Effects03:26

Framing Effects

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Information is everywhere and its presentation—such as how and when items are presented—can impact our perceptions and decisions surrounding the info. This broad concept umbrellas framing effects—influences that occur due to the way information is framed in its appearance, whether it’s purely the order or the specific wording of a message. Let’s take a look at numerous ways in which two versions of something can objectively say the same thing, yet we respond in...
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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相关实验视频

Updated: Jun 28, 2025

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
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在Fermatean模糊的双极软框架下的多属性决策.

Ghous Ali1, Masfa Nasrullah Ansari1

  • 1Division of Science and Technology, Department of Mathematics, University of Education, Lahore, Pakistan.

Granular computing
|April 16, 2024
PubMed
概括
此摘要是机器生成的。

费尔马特的模糊集合理论提供了一种管理不确定性的新方法. 这项研究引入了费尔马特模糊双极软集模型,增强了复杂场景中的决策.

关键词:
算法算法是一种算法.决策方式 决策方式费尔马特人模糊的双极软集双极软集费尔马特的模糊集是一个模糊集.评分函数是一个评分函数.

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An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
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科学领域:

  • 数学 数学 是一个数学.
  • 计算机科学 计算机科学
  • 决策科学 决策科学 决策科学

背景情况:

  • 费尔马特模糊集合为处理不确定性提供了一个强大的框架,优于直觉主义和毕达哥拉斯模糊集合.
  • 现有的模糊集模型在捕捉不确定性下的真实世界决策细微差别方面存在局限性.

研究的目的:

  • 介绍和研究新的费尔马特模糊双极软集 (FFBSS) 模型.
  • 扩展现有的模糊双极软集和毕达哥拉斯模糊双极软集模型.
  • 探索FFBSS模型在多属性决策 (MADM) 中的适用性.

主要方法:

  • 开发了FFBSS模型的基本属性,包括子集,平等和运算 (交叉,联盟,AND,OR).
  • 拟议的基本操作,如FFBSS.的Fermatean模糊加权平均值和得分函数.
  • 使用了一种新的算法来支持MADM问题的 FFBSS 方法.

主要成果:

  • 研究和定义FFBSS模型的关键属性和操作,并提供数值示例.
  • 通过两个不同的MADM应用程序证明了FFBSS模型的有效性.
  • 提供了比较分析,突出了FFBSS与现有模型的优势.

结论:

  • FFBSS模型提供了一种更灵活,更可靠的方法来处理决策中的不确定性.
  • 拟议的模型及其相关操作对于各种多属性决策问题是有效的.
  • 在复杂的现实应用中,FFBSS代表了模糊集合理论的重大进步.