This is a Fuzzy Ready Here is the very informative Inference Systems/Mamdani's Methods/Fuzzy Logic Toolbox quiz. Fuzzy inference is the process of constructing the mapping from a given input to output using fuzzy logic, which has been applied in various fields such as automatic control, data classification, decision analysis, expert systems, and computer vision. It is associated with a number of names such as fuzzy-rule-based systems, fuzzy expert systems, fuzzy modeling, fuzzy associative memory, fuzzy logic controllers. Try out the quiz and further enhance our knowledge. All the best!
The process of formulating the mapping from a given input to an output using fuzzy logic
Changing the output value to match the input value to give it an equal balance
Having a larger output than the input
Having a smaller output than the input
Model-Type and System-Type
Momfred-Type and Semigi-Type
Mamdani-Type and Sugeno-Type
Mihni-Type and Sujgani-Type
Wireless services, heat control, and printers.
Restrict power usage, telephone lines, and sort data.
Simulink, boiler, and CD recording.
Automatic control, decision analysis, and data classification.
Fuzzy Expert System
Fuzzy Modelling
Fuzzy Logic Controller
All of the above
Control any two combinations of any two products by synthesizing a set of linguistic control rules obtained from experienced human operations.
Control a television and remote combination by synthesizing a set of linguistic control rules obtained from experienced human operations.
Control a steam engine and a boiler combination by synthesizing a set of linguistic control rules obtained from experienced human operations.
Control an air craft and fuel level combination by synthesizing a set of linguistic control rules obtained from experienced human operations.
Fuzzification of the input variables
Defuzzification
Application of the fuzzy operator (AND or OR) in the antecedent
Aggregation of the consequents across the rules
The input is a single truth value, and the output has two or more values.
The input is a value greater than one, and the output is a value less than the input.
The input and output have both the same values.
The input has two or more values, and the output has a single truth value.
Probor (a,b) = a-b + ab
Probor (a,b) = ab + ab
Probor (a,b) = a+b - ab
Probor (a,b) = a/b x ab
Input is a fuzzy set, but the output is a whole value.
Input is a whole value, but the output can be a fuzzy set.
Input and output have the same value.
Input is a smaller value than the output value.
To gather all the different fuzzy set outputs and combine them into a single fuzzy set outputs.
To gather all the possible inputs and use the average to gain an output.
To gather all the different fuzzy set outputs and average them out to get a single value.
To subtract all the output fuzzy set values from the input values.