Abstract
Information granules, along with their processing constitute a core of granular computing, which provides a unified conceptual and algorithmic framework for designing and analyzing intelligent systems. In this study, we engage a principle of justifiable granularity as a way of forming type-1 and type-2 information granules-granular interval-valued information granules, whose descriptors are intervals themselves rather than numeric entities. A two-phase design process is presented: first, intervals (viz. information granules of type-1) are constructed based on available experimental data. Second, considering the data that have not been "covered" by the intervals (the data one can refer to as residual granular data), we construct their bounds in the form of information granules (instead of numeric values) thereby giving rise to the concept of granular intervals, namely information granules of type-2. A series of experiments are provided that focus on sensor fusion formed with the aid of information granules and granular system modeling of type-1 and type-2.