Exact(1)
In our case, for each variable to be fuzzified, we chose the minimum, the median and the maximum values of the observed non-null values.
Similar(59)
Note that the significant characteristic of fuzzy logic is that a numerical value does not have to be fuzzified using only one membership function.
In general, the inputs for the fuzzy inference system (FIS) need to be fuzzified or categorized into levels or degrees such as low, medium, and high.
Even the act of breathing is a variable to be negotiated.
The input from risk assessment models (or even practice guidelines) could be fuzzified for variables that are compatible with this way of thinking.
This set will be fuzzified, resulting in joint, fuzzy representation of the merged patterns.
Firstly, the current state λ u should be fuzzified into a fuzzy set s.
In this layer, each input variable is fuzzified into three linguistic levels - high (H), medium (M), and low (L) - which are also called Gaussian fuzzy sets.
At first the input and output variables have been fuzzified in the fuzzification process.
First, the numerical input variables (occurrence, severity) are fuzzified using appropriate MFs.
Each of the two output variables of RL-FNN is fuzzified into three linguistic levels - high (H), medium (M), and low (L).
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Justyna Jupowicz-Kozak
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