Influence of Fuzzification Method to System Behavior

Many different fuzzification methods are quoted in the literature. Two frequently used methods were introduced above. These methods influence system behavior. That means not only an effect on output value but it introduces some nonlinearity into the system. The FUZZY_AND is often realized as minimum method. This is simple and easy to understand. But sometimes this method introduces some strange behavior in the model. The minimum function cuts the values very strongly. This is sometimes undesirable. The use of the FUZZY_AND Prod is often a better choice. This produces a smoother functional behavior and should be preferred in practical simulations.

Figure 2 Fuzzy AND Min, x-axis: coverage degree, mean distance to structure = 130m.

Figure 2 Fuzzy AND Min, x-axis: coverage degree, mean distance to structure = 130m.

This was checked with the fuzzy model for the nutrition quality for the lesser spotted eagle, aquila pomarina (see below). At first the chart of the model using FUZZY_AND Min was plotted in Figure 2.

Easily visible is the vertex in the upper part of the chart. This can be changed with the use of the FUZZY_AND Prod. This is shown in Figure 3. The last chart looks smoother than the first one.

If the fuzzy model is checked, it can be used as part of a habitat model in a simulation.

Figure 3 Fuzzy AND Prod, x-axis: coverage degree, mean distance to structure = 130m.

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