In this paper a new technique for eliciting a fuzzy inference system (FIS) from data for nonlinear systems is proposed. The strategy is conducted in two phases: in the first one, subtractive clustering is applied to extract a set of fuzzy rules, in the second phase, the generated fuzzy rule base is refined and redundant rules are removed on the basis of an interpretability measure. Finally, cen...

This paper presents a proposition of the knowledge representation and the inference procedure including two types of uncertainty: probabilistic and fuzzy. Added weights to the fuzzy rule-based model state probabilities of fuzzy events in antecedents and consequents. The exemplary calculations are presented. Key-Words: Fuzzy sets, Knowledge representation, Inference procedure, Probability of fuz...

Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS) concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn from a set of sample data could improve the performance of Existing traffic signal controlling sy...

AB STRACT. The role of inferencing with uncertainty is becoming more important in rule-based expert systems (ES) , since knowledge given by a human expert is often uncertain or imprecise. We have succeeded in designing a VLSI chip which can perform an entire inference process based on fuzzy logic. The design of the VLSI fuzzy inference engine emphasizes simplicity, extensibility, and efficiency...

  Selection of appropriate infrastructure transportation projects such as highways, plays an important role in promotion of transportation systems. Usually in evaluation of transportation projects, because of lack of information or due to long time and high expenditures needed for gathering information, different effective factors are ignored. Thus, in this research, regarding multi criteria na...

In this paper, we present an evolutionary multiobjective learning model achieving cooperation between the rule base and the adaptive fuzzy operators of the inference system in order to obtain simpler, more compact and still accurate linguistic fuzzy models by learning fuzzy inference adaptive operators together with rules. The multiobjective evolutionary algorithm proposed generates a set of fu...

Imprecise inference models the ability to infer sets of values or information chunks. Imprecise database inference is just as important as precise inference. In fact, it is more prevalent than its precise counterpart even in precise databases. Analyzing the extent of imprecise inference is important in knowledge discovery and database security. Imprecise inference analysis can be used to \mine"...