Given that the analysis relevant to the present investigation presents vague or imprecise edges, the consensus between <A>, <Neut-A>, <Anti-A> and <Non-A> is analyzed, through a study supported by the fuzzy model
The results obtained using the fuzzy model
ranged from a value of 3.1 for the area identified by Ramos et al.
The structure generated by the fuzzy model
have used three membership functions for each input: fine particulate matter ([PM.sub.2,5]), temperature (TEMP) and three output membership functions (number of hospitalizations) (Figure 2).
The regression analysis performed on the data gave an R-squared factor of 0.92 for the fuzzy model
and 0.78 for the actual data.
Since in the process of constructing fuzzy model
with the best classification; the number of parameters that need to be adapted in the most appropriate way, which is also called the "dimension problem", increases as the number of independent variables increases.
to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock.
The optimum results of the fuzzy model
are defuzzified by the signed distance method.
After fuzzy model
was developed, a defuzzification we performed in order to obtain 3D output parameter plot.
However, the main problem with the fuzzy model
is that there is no systematic procedure to define the membership function parameters, which must be predetermined by expert knowledge about the modeled system.
Recently, the T-S fuzzy model
has been extended to polynomial fuzzy model
The Takagi-Sugeno-based fuzzy model
is helpful to achieve consequence parameters based on the least square method.