### Table 1 An a priori fuzzy rule base

"... In PAGE 15: ...2 Fuzzy control using an a priori fuzzy model Because the rocket velocity will increase as the velocity of the exhaust gases increases, a rule base can be constructed a priori based only on logical consid- erations. Table1 shows this three-dimensional rule base as a sequence of two- dimensional tables, and for each of them variable C takes a different value. This rule base can be used as a starting point in the control/identification process, so that the modifications required in the learning process are applied over it.... ..."

### Table 1. Fuzzy rule base for person recognition

"... In PAGE 9: ... 8. Architecture of the fuzzy system for person recognition We show in Table1 the complete set of fuzzy rules used in the fuzzy system for person recognition. Table 1.... ..."

### Table 3 Rule-base of the auxiliary fuzzy system for the output scale factor (Fadapt_output)

2006

"... In PAGE 8: ...which initially is set to 0.5, i.e., 50% of the maximum heating power). Therefore, no pre-training is conducted on our advanced fuzzy system. Table3 shows a typical rule-base of the fuzzy auxiliary system for the adaptation of the output scale factor. As inputs, this fuzzy system uses the temperature of the room and its variation, with seven evenly distributed triangular functions for the former and five for the latter, forming a triangular partition.... ..."

### Table 1. Data sets used in this paper and some reported results by fuzzy rule-based systems.

"... In PAGE 9: ... (22) 4. Computational Experiments In our computational experiments, we used four data sets in Table1 available from the UCI ML repository. For comparison, some reported results by fuzzy rule-based systems are also included in Table ... In PAGE 16: ...0 1.48 1.40 1.33 1.44 1.10 1.00 1.77 1.94 1.95 1.85 1.87 Let us examine our experimental results in detail. First we compare our results with the reported results by fuzzy rule-based systems in Table1 . For the glass data set in Table 3, a 42.... In PAGE 16: ...evel 0.7. This average result is almost the same as a 42.1% average error rate in Table1 by 8.5 fuzzy rules in Sanchez et al.... In PAGE 16: ... This average result is almost the same as a 4.65% error rate in Table1 by 5.... In PAGE 16: ...eported result (i.e., a 3.24% average error rate by 5.2 fuzzy rules; see Table1 ) in Castillo et al. (2001).... In PAGE 20: ... Thus the number of candidate rules should be appropriately specified. From the comparison of our results in Table 16 with the reported results in the literature in Table1 and Table 2, we can see that very good results were obtained by the genetic algorithm-based rule selection for the Wisconsin breast cancer data (a 3.25% average error rate) and the sonar data (i.... ..."

### Table 2 Rule-base for the classical fuzzy system, obtained and tuned by trial and error

2006

"... In PAGE 6: ... Both the classical and the advanced fuzzy controllers have two inputs, one is the error of the temperature and the other one is the first derivative of the error of the temperature. Table2 shows the rules used for the classical fuzzy controller, which have been obtained and optimized by trial and error for the given plant, and Fig. 3 its input and output membership functions.... ..."

### Table 1. Fuzzy rule base for fuzzy system 1.

### Table 2. Table 2. Fuzzy rule base for fuzzy system 2.

### Table 3. Fuzzy rule base for fuzzy system 3.

### Table 2. Integer table for the rule base of the aircraft landing control system

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"... In PAGE 7: ...The integer table in Table2 shows clearly that the information from the rule base in Equation (3) has been significantly compressed whereby all unnecessary details have been removed. This type of compression reduces the complexity of the fuzzy system without compromising its quality.... ..."