Hi Rudy,
The Fuzzy Logic Toolbox in MATLAB is designed to handle uncertainty and imprecision, which makes it suitable for dealing with inputs that may sometimes be unknown or partially known. When working with fuzzy systems, you can model such uncertainties using fuzzy sets and rules. Here’s how you can handle unknown values or missing inputs in the Fuzzy Logic Toolbox:
Default Values:
- Assign a default value to the input when it's unknown. This default value could be the mean, median, or any other representative value based on historical data or expert knowledge.
Fuzzy Sets for Uncertainty:
- Define a fuzzy set that represents an unknown or uncertain state. For example, you could have a fuzzy set named "Unknown" or "Uncertain" that covers a wide range of possible values.
Fuzzy Rules for Missing Inputs:
- Create rules that account for missing or unknown inputs. For instance, if temperature is unknown, you might have a rule that uses other known inputs to estimate the output.
Handling Missing Data:
- Use techniques to handle missing data before feeding it into the fuzzy system. This could involve data imputation methods or statistical techniques to estimate the missing values.
Hope this helps.
