模糊逻辑系统

As discussed earlier, the Fuzzy Logic System consists of 4 components: the Knowledge Base, Fuzzification Module, Inference Engine, and the Defuzzification Module. We know how the data and information flow between these components, but we do not know how the processing of that information takes place. Here, we are going to study the same.

如前所述， 模糊逻辑系统由4个组件组成：知识库，模糊化模块，推理引擎和模糊化模块。 我们知道数据和信息在这些组件之间的流动方式，但是我们不知道该信息的处理方式。 在这里，我们将进行同样的研究。

会员功能 (Membership Function)

The membership function is the backbone of the Inference Engine. It is a function which quantifies the data and represents a Fuzzy Set, which is defined over the range 0 to 1 (both inclusive). The input space that the Membership Function works in is known as the Universe of Discourse and the data that it takes as input are usually linguistic terms.

隶属函数是推理引擎的基础。 它是一种量化数据并表示模糊集的函数，该模糊集在0到1(包括两者)的范围内定义。 隶属函数在其中起作用的输入空间被称为“话语宇宙”，而它作为输入的数据通常是语言术语。

The Linguistic terms can be defined as the words which define the physical characteristics of a function. For example, if we are defining the temperature of a body, then we use the terms which define the characteristics of it, like high, low, very high, moderate, etc. These are the linguistic terms here.

语言术语可以定义为定义功能的物理特征的单词。 例如，如果我们要定义一个物体的温度，那么我们将使用定义该物体特征的术语，例如高，低，非常高，中等等。这些是这里的语言术语。

The Membership function can be defined as: µ_P: X → [0, 1]

隶属度函数可以定义为： µ _P ：X→[0，1]

Where,

哪里，

• 'µ' denotes the membership function,

  “ µ”表示隶属函数，

• 'P' denoted the Fuzzy Set,

  “ P”表示模糊集，

• and 'X' denotes the universe of discourse, i.e. input space.

  “ X”表示话语的宇宙，即输入空间。

Algorithm:

算法：

The algorithm on which the Fuzzy logic system is as follows:

模糊逻辑系统的算法如下：

1. Define the Knowledgebase by feeding the Fuzzy set Rules into it.

   通过将模糊集规则输入知识库来定义知识库。

2. Define the universe of discourse for the membership function.

   定义隶属函数的话语范围。

3. Construct the membership function (By any method, Triangular, Singleton or Gaussian).

   构造隶属函数(通过任何方法，使用Triangular，Singleton或Gaussian)。

4. Perform Fuzzification to convert the input information into data in the form of Fuzzy sets.

   执行模糊化以将输入信息转换为模糊集形式的数据。

5. Process the Fuzzy data set and draw the inference using the rules defined in the Knowledgebase (This process takes place inside the Inference Engine).

   使用知识库中定义的规则处理模糊数据集并得出推理(此过程在推理引擎内部进行)。

6. Perform Defuzzification to convert the fuzzy data into the user-understandable form and produce the output.

   执行“去模糊化”以将模糊数据转换为用户可理解的形式并产生输出。

翻译自: https://www.includehelp.com/ml-ai/working-inside-the-fuzzy-logic-system-artificial-intelligence.aspx

模糊逻辑系统