An improved multidimensional alpha-cut based fuzzy interpolation technique

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered by sparse rule bases. In most engineering applications, the use of more than one input variable is common. This paper proposes an improved multidimensional fuzzy rule interpolation technique to handle large dimensional input spaces. Illustration examples are also generated and results shown that this improved multidimensional α-cut based fuzzy interpolation technique can be used in engineering applications.