Fuzzy inference abilities were implemented to electromagnetic problems for the first time by the authors. After very successful results of applying the developed fuzzy modeling method to input impedance of a general monopole antenna, in this paper classifying the engineering electromagnetic problems simply, we apply the abilities of the proposed fuzzy inference method to make a qualitative model for transmission lines as a general example for a certain category of problems. The proposed approach starts from observing the problem through the window of human direct understandings and uses some parameters (as calculation base) evaluated basic for modeling process. It is shown that because of using this novel view point, a very simple fuzzy system based on new parameters may model the behavior of a transmission line in general form. The knowledge of each variable can be extracted and saved as simple curves individually, through continuing to make several models considering the desired variable as parameter. Finally, it is shown that the proposed method works even in highly nonuniform transmission line cases without changing in structure and complexity.

The abilities of fuzzy inference methods in modeling of complicated systems are implemented to electromagnetics for the first time. The very popular and well known monopole antenna is chosen as a general example and a fast, simple and accurate fuzzy model for its input impedance is made by introducing a new point of view to impedance basic parameters. It is established that a surprisingly little number of input data points is sufficient to make a full model and also the system behavior (dominant rules) are saved as simple membership functions. The validity of the derived rules is confirmed through applying them to the case of thin-angled monopole antenna and comparing the results with the measured. Finally using the spatial membership function context, input impedance of thick-angled monopole antenna is predicted and a novel view point to conventional electromagnetic parameters is discussed to generalize the modeling method.