transformationsnormalization
Transformationsnormalization, often abbreviated as T-Norm normalization, is a mathematical technique used in the fields of fuzzy logic and data processing to standardize or normalize the results of transformations applied to data sets or fuzzy rules. Its primary purpose is to ensure consistency and comparability of data by adjusting values within a specific range, typically between 0 and 1, or within a defined scale. This process facilitates meaningful comparisons and decision-making based on fuzzy logic systems or other probabilistic models.
In fuzzy logic, transformations are operations applied to fuzzy membership functions or variables, often to modify
The normalization process involves mathematical functions that adjust the values from a transformation, maintaining the relative
Transformationsnormalization is a key component in designing fuzzy inference systems, facilitating the integration of multiple data