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Today, the editor brings you the part of the MULTIMOORA multi-attribute decision-making method of "Multi-attribute Decision-making Methods and Application Research Considering Decision-Maker Behavior in Probabilistic Language Environment".
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Today, the editor brings the MULTIMOORA method of the article "Research on multi-attribute decision making method and its application considering decision makers' behavior in probabilistic linguistic environment".
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1 内容摘要（Content summary）
Today, the editor will interpret and share the MULTIMOORA multi-attribute decision-making method part of "Multi-attribute Decision-making Methods and Application Research Considering Decision-Maker Behavior in Probabilistic Language Environment" from the three sections of "Mind Map, Intensive Reading Content, and Knowledge Supplement".
Today, the editor will interpret and share the MULTIMOORA method of the article "Research on multi-attribute decision making method and its application considering decision makers' behavior in probabilistic linguistic environment" from the three sections of "mind map, intensive reading content, and knowledge supplement".
2 思维导图（Mind mapping）
3 精读内容（Intensive reading content）
In the fifth chapter of the article, the author introduces a new multi-attribute decision-making method.
In this issue, the featured reading arrives at the fifth chapter, introducing a new chapter where the author discusses a novel multi-attribute decision-making method.
In this chapter, the author introduces the multi-attribute decision-making method of MULTIMOORA, a probabilistic language term set based on the theory of cumulative prospects, and applies it to the actual evaluation of the teaching quality of college education.
In this chapter, the author introduces the MULTIMOORA multi-attribute decision-making method based on cumulative prospect theory's probability language terms and applies it to the practical assessment of higher education teaching quality.
The author first introduces the theory of cumulative prospects. The cumulative prospect theory is an improvement of the prospect theory, which weights the cumulative weighting function as a whole to calculate the decision weight, replaces the probability in the traditional expected utility function, and expands the scope of application of the prospect theory.
The author begins by introducing cumulative prospect theory, an improvement upon prospect theory. It involves overall weighting of cumulative prospect functions for decision weight calculation, replacing the probabilities in traditional expected utility functions, thus expanding the applicability of prospect theory.
The cumulative prospect theory is an improved version of the prospect theory, and today it is considered a valid alternative to the classical expected utility theory. The cumulative prospect theory suggests that when decision-makers make decisions under risk, they set a reference point that treats smaller outcomes as losses and larger outcomes as gains.
Cumulative prospect theory is an improved version of prospect theory and is now considered an effective alternative to classical expected utility theory. It suggests that decision-makers, when making decisions under risk, set a reference point, considering smaller outcomes as losses and larger outcomes as gains.
The cumulative prospect theory retains the basic ideas of the classical expected utility theory of descriptive ability-rank correlation utility and Choquet expected utility, but some scholars have questioned this theory, the most important of which is the separability of gain loss.
Cumulative prospect theory retains the descriptive power of classical expected utility theory and the basic ideas of rank-related utility and Choquet expected utility. However, some scholars have questioned this theory, with the most significant being the issue of gain-loss separability.
The cumulative prospect theory uses the cumulative probability to calculate the decision weight, instead of using a single probability to calculate, including two parts: the value function and the weight function.
Cumulative prospect theory uses cumulative probabilities for decision weight calculation instead of relying on individual probabilities, including both value and weight functions.
On the basis of the cumulative prospect theory, the decision-maker will evaluate the original information, and then the decision-maker's behavior and psychological preferences can be considered to form the corresponding decision-making weight to judge the decision-maker's decision-making. In the decision-making process, the decision-maker will propose a difference to the risk appetite based on the average risk level expected at the reference point to reflect the decision-maker's preference for gains or losses.
Building upon cumulative prospect theory, decision-makers evaluate raw information, considering their behavioral and psychological preferences to form corresponding decision weights, enabling judgment of the decision-maker's decisions. During the decision-making process, decision-makers assess the expected risk level around the reference point, express differences in risk preferences to reflect preferences for gains or losses.
4 知识补充（Knowledge supplement）
WHAT IS THE MULTIMOORA METHOD?
What is the MULTIMOORA method?
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https://blog.csdn.net/weixin_44014836/article/details/123964391
Reference: Yang Yaxu. Research on multi-attribute decision-making methods considering decision-makers' behaviors in probabilistic language environment and their applications[D]. Baoding: Hebei University, 2023.
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