fuzzy comprehensive evaluation method

Fuzzy Comprehensive Evaluation Method

Fuzzy comprehensive evaluation method is a system of evaluating variables in a specified field that accounts for various levels of uncertainty and subjectivity. The method was first proposed by Zadeh, who argued that it was possible to express fuzzy sets in the form of a mathematical equation. The concept has since been extended to the evaluation of a variety of different fields, from economics to construction.

The main benefit of using the fuzzy comprehensive evaluation method is that it enables the evaluation of variables that are difficult to measure precisely. This is because the method allows for the incorporation of subjective criteria in the evaluation, as well as taking into account different levels of uncertainty. For example, when evaluating a construction project, one may consider the financial impact of the project, the environmental impact of the project, and the potential impact on society. By utilizing the fuzzy comprehensive evaluation method, these criteria can be taken into account, allowing the evaluator to arrive at an accurate and meaningful evaluation.

The method of fuzzy comprehensive evaluation works by establishing various levels of certainty, with each level having a specific weight. Each variable is then assigned a numerical value based on its level of certainty. The numerical value of each variable is then multiplied together to arrive at an overall score. This score allows the evaluator to determine which of the variables should receive the most attention in the overall evaluation.

A variety of different methods can be used to determine the numerical value associated with each variable within a given field. One common method is the “fuzzy inference” method, which involves assigning values to variables based on the likelihood that they possess a certain property. For example, in the construction field, variables such as cost, time, and quality can be assigned values according to their likelihood of achieving the desired outcome. The higher the value of each variable, the more likely it is to receive a high overall score.

Fuzzy comprehensive evaluation can be used to evaluate a wide range of variables, from construction projects to economic models. It is especially useful for evaluation projects that involve multiple variables, since it allows for the incorporation of subjective criteria and levels of uncertainty. By enabling evaluators to self-determine their levels of certainty, the method can help them to make more accurate and meaningful evaluations. This can be helpful in a variety of situations, such as determining the best way to approach a given problem or considering how various solutions can be applied to a particular issue.

Fuzzy Comprehensive Evaluation Method

Fuzzy comprehensive evaluation method is a comprehensive evaluation method which uses fuzzy reasoning technology to realize subjective evaluation combining with fuzzy mathematics. Fuzzy comprehensive evaluation method has been widely used in many industries such as government decision-making, industrial research, quality control, management science and so on.

Fuzzy comprehensive evaluation method can solve decision-making problems which are difficult for traditional methods because of its ability to deal with uncertainty, which is a property of a decision problem. In this evaluation method, the experts are required to provide subjective qualitative evaluation on the evaluation objects.

In fuzzy comprehensive evaluation method, the input variables are linguistic expressions or numerical intervals, and the output variables are numerical values. The entire process can be divided into three parts: (1) expert evaluation; (2) transformation of linguistic knowledge; (3) evaluation result calculation.

In the first part, that is, expert evaluation, we obtain the opinions of experts on this system by questionnaires or interviews, and their views are generally expressed in the form of linguistic variables and their membership functions. In the second part, that is, the transformation of linguistic knowledge, the linguistic variables and the membership functions obtained by experts are converted into the corresponding fuzzy subsets, that is, the fog data.

In the third part, that is, the calculation of evaluation results, when we have the fog data, we can use a series of principles and methods of inference to infer the fuzzy evaluation values of decision attributes according to the established coefficient model. Finally, we obtain the fuzzy comprehensive evaluation results.

Fuzzy comprehensive evaluation method has been widely used and has good results in many application fields, but it also faces some shortcomings, such as lack of proper evaluation standards and difficulty in determining the importance of decision elements objectively. Although it has some shortcomings, the fuzzy comprehensive evaluation method is still a valuable tool for dealing with uncertainty.