Widely popular cases of fuzzy rule interpolation techniques

To handle the inevitable problem of exponential calculation time and storage-space complexity of fuzzy logic algorithms, fuzzy interpolation methods have been proposed as a possible reduction technique. They form an inference engine that is applicable, unlike classical fuzzy algorithms, even in an uncompleted knowledge base when the rules are sparse. The paper compares the KH, the modified KH, VKK and the general fuzzy interpolation methods for the widely popular cases of triangular and trapezoidal sets.