Approximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then
rules in which attribute values are imprecisely described. Fuzzy rule interpolation (FRI) …

Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …

E-government is an indispensable part of a Smart City. Information and communication
technologies transform the relationship between citizens, businesses, and government …

Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in
sparse rule-based systems (and also for reducing the complexity of fuzzy models). However …

A rule base covering the entire input domain is required for the conventional Mamdani
inference and Takagi–Sugeno–Kang (TSK) inference. Fuzzy interpolation enhances …

Fuzzy rule-based models (FRBMs) are sound constructs to describe complex systems.
However, in reality, we may encounter situations, where the user or owner of a system only …

From a neo-institutional perspective, this chapter investigates the function and interaction of
globalization and decentralization in China's higher education administrative reform. Both …

Fuzzy rule interpolation (FRI) is of particular significance for reasoning in the presence of
insufficient knowledge or sparse rule bases. As one of the most popular FRI methods …

Big data refers to large complex structured or unstructured data sets. Big data technologies
enable organisations to generate, collect, manage, analyse, and visualise big data sets, and …

Using fuzzy rule interpolation (FRI) interpolative reasoning can be effectively performed with
a sparse rule base where a given system observation does not match any fuzzy rules. While …