What I am supposed to write in this question about fuzzy logic?

[shivajikobardan]

There are 2 questions commonly asked(rarely though) in my exams.
1) Explain about mamdani fuzzy inference method with example.

2) explain fuzzy inference with suitable example.

Now I am self studying. I have 4 books with me, but none of them have this content. IDK why tho..There are other details but not about thse 2 questions. Can you just guide me what I am supposed to write here? A framework about what to write would be more than helpful to me.

 

[Future Bruno]

Mamdani Fuzzy Inference MethodThe Mamdani fuzzy inference method is a form of fuzzy logic that uses an “if-then” approach to create a set of rules that can be used to make decisions. This method is based on the premise that each input variable has a range of values and a corresponding set of fuzzy sets that describe the degree to which the input variable is similar to each of the fuzzy sets. The fuzzy sets are then used to generate a set of rules that define the relationships between the inputs and the outputs.An example of a Mamdani fuzzy inference system is a temperature controller. In this system, the input variables are temperature readings from a thermometer and the output variable is the desired temperature setting. The fuzzy sets used in this system would describe the various degrees of similarity between the input and output variables, such as high, medium, low, etc. The fuzzy sets are then used to generate a set of rules that define the relationship between the temperature readings and the desired temperature setting.Fuzzy InferenceFuzzy inference is a process of making decisions based on fuzzy logic. It is a form of artificial intelligence that uses fuzzy logic, which is based on the principle that all information is incomplete or imprecise. Fuzzy logic allows a computer to accept imprecise statements and use them to make decisions or provide answers. An example of fuzzy inference is a system that can recognize images. In this system, the input variables are the image data and the output variable is the recognition result. The fuzzy sets used in this system would describe the various degrees of similarity between the input and output variables, such as high, medium, low, etc. The fuzzy sets are then used to generate a set of rules that define the relationships between the image data and the recognition result. The fuzzy inference system then makes a decision based on these rules and provides the appropriate recognition result.