ai系统架构_人工智能中的模糊逻辑系统架构

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The Fuzzy Logic System is a system which uses Fuzzy logic for reasoning. Fuzzy Logic is a very efficient method for performing human-like reasoning in conditions with uncertainty.

模糊逻辑系统是使用模糊逻辑进行推理的系统。 模糊逻辑是一种在不确定条件下执行类似人的推理的非常有效的方法。

If we take a look at the architecture of the Fuzzy Logic system, then we find that it is composed of the following four major parts:

如果我们看一下模糊逻辑系统的体系结构 ，那么我们发现它由以下四个主要部分组成：

1. Knowledge Base

   知识库

2. Fuzzification Module

   模糊化模块

3. Inference Engine

   推理机

4. Defuzzification Module

   解模糊模块

Now, let us have a look at each of them one by one:

现在，让我们逐一查看它们：

1)知识库 (1) Knowledge Base)

Every system which works on Artificial Intelligence has a Knowledgebase. The Fuzzy logic system is also an AI-based system, and thus it also has its own knowledge base where all the information and data for the reference by the agent is stored. In the Knowledge Base of Fuzzy Logic system, the rules of the Fuzzy Logic set theory are stored. Their rules are present in the form of an if-else ladder. So, whenever the system tries to solve any problem, this if-else ladder is executed and the system then works on the rule that it gets from the matched condition.

每个在人工智能上运行的系统都有一个知识库。 模糊逻辑系统也是基于AI的系统，因此它也具有自己的知识库，该知识库存储了供代理参考的所有信息和数据。 在模糊逻辑系统的知识库中，存储了模糊逻辑集合论的规则。 他们的规则以if-else阶梯的形式出现。 因此，每当系统尝试解决任何问题时，都会执行此if-else梯形图，然后系统根据从匹配条件获得的规则进行工作。

2)模糊化模块 (2) Fuzzification Module)

The fuzzification module performs the conversion of the input information. The information is converted into a form which the system can search for in its Knowledge Base. This is done by splitting the sentences into simpler terms and extracting the main terms out of it which are then sent to the inference engine for further processing.

模糊化模块执行输入信息的转换。 信息将转换为系统可以在其知识库中搜索的形式。 这是通过将句子分成更简单的术语并从中提取主要术语来完成的，然后将其发送到推理引擎进行进一步处理。

3)推理机 (3) Inference Engine)

The Inference engine is the main component of the Fuzzy Logic System. If compared with the computer parts, our inference engine is the same as the processor of the computer. All the processing of the information takes place inside it. The task of the inference engine is to draw a valid result by analyzing and concluding all the information that it gets from the fuzzification module. This is again done by referring to the rules and prior information present in the Knowledge Base. The final conclusions made are then sent for further modification to the defuzzification module.

推理引擎是模糊逻辑系统的主要组件。 如果与计算机部件进行比较，我们的推理引擎与计算机的处理器相同。 信息的所有处理都在其中进行。 推理引擎的任务是通过分析和总结从模糊化模块获得的所有信息来得出有效的结果。 再次通过参考知识库中的规则和现有信息来完成此操作。 然后将得出的最终结论发送给去模糊化模块进行进一步修改。

4)解模糊模块 (4) Defuzzification Module)

The Defuzzification Module receives the processed information from the Inference Engine. This information contains the conclusion, but still, it is not in the form in which it was received, i.e. user-understandable form. So, the defuzzification module again converts this information into a form which is well accepted by the user.

去模糊化模块从推理引擎接收处理后的信息。 该信息包含结论，但仍然不是以其接收的形式，即用户可理解的形式。 因此，去模糊化模块再次将该信息转换为用户很好接受的形式。

翻译自: https://www.includehelp.com/ml-ai/fuzzy-logic-system-architecture-in-artificial-intelligence.aspx

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