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ฐานองคความรูฟซซีสามารถแสดงไดเปน Rule 1: If feature1 is high and feature2 is low and feature3 is medium, then class is 1 with confident CF1; Rule 2: If feature1 is medium and feature2 is low and feature3 is then class is 3 with confident CF2; Rule 3: If feature1 is high and feature2 is high and feature3 is medium, then class is 2 with confident CF3. ตัวอย่าง
Simulated 3-Class 2-Dimension Problem This simulated problem is a linearly separable 3-classe 2-dimension pattern space. There are 80 patterns all together generated. Class 1 has 20 patterns; class 2 has 20 patterns; and class 3 has 40 patterns. The plot of this data set is shown below. ตัวอย่าง
For a 3-class, 2-dimension problem above, if we use 2 fuzzy linguistic label, small and large, we can construct a 4, i.e., 22, fuzzy rules for a fuzzy expert system as: Rule 1: If x1 is small and x2 is small then class is 2 (×). Rule 2: If x1 is small and x2 is large then class is 1 (ο). Rule 3: If x1 is large and x2 is small then class is 3 (Δ). Rule 4: If x1 is large and x2 is large then class is 3 (Δ). This can be automatically generated by using the ILFN classifier and then use “ilfn2rule” to map the ILFN weight to fuzzy if-then rules. ตัวอย่าง