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There are various materials selection methods like Ashby's method or digital logic methods such as DL and MDL.
Neural methods can be incorporated into fuzzy systems and fuzzy logic methods can be introduced into neural networks to take advantage of their complementary characteristics.
A designed NSGA-II, C-METRIC and fuzzy logic methods were developed to solve the above multi-objective integer nonlinear programming model.
Universal knowledge based approximators comprising of neural networks and fuzzy logic methods are capable of approximating the nonlinearities and the uncertainties of practical systems.
Such systems combine the merits of both fuzzy logic systems and neural networks; namely, the explicit knowledge representation from fuzzy logic methods and the learning ability of neural networks.
However, traditional drawbacks in fuzzy logic methods exist in the proposed fuzzy logic approach.
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In development projects, logical frameworks are the predominant program logic method used and are particularly important as communication tools in projects that cover diverse countries, cultures and languages [ 16].
The results showed that the average prediction error was 6.97%, better than the Fuzzy logic method.
To find the best solution for the non-dominated results, a fuzzy logic method is employed.
Induction, in logic, method of reasoning from a part to a whole, from particulars to generals, or from the individual to the universal.
Based on selected qualitative features, motor's quality types are determined by using the fuzzy logic method.
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