Membership degree is an important concept in fuzzy mathematics, which is used to measure the degree to which an element belongs to a fuzzy set. In fuzzy logic, each element can belong to multiple fuzzy sets at the same time, and its membership degree indicates the degree to which it belongs to these sets. When an element has the greatest degree of membership to a set, it means that it has the closest connection with the set and is the most typical representative of the set.

As a tool to measure fuzziness, membership degree is widely used in practical applications. For example, in the control of traffic lights, the degree of membership can be used to determine the timing of stopping or passing vehicles; In medicine, the degree of membership can be used to evaluate the severity of diseases; In economics, membership can be used to help enterprises determine business parameters such as market share.

To calculate the membership degree of an element to a fuzzy set, it needs to be calculated by the membership function in fuzzy logic. Different membership functions have different mathematical expressions, and their area is the membership degree of elements to a set. Common membership functions are Gaussian function, trigonometric function and so on. In addition, the membership degree of elements can be determined by fuzzy clustering and other algorithms.