In the real world, phenomena are often observed and recorded by multiple organizations
which results in multiple sources of data. When dealing with such data, the centralized …

In this study, an interval information granulation-based fuzzy partition (InterIG-FP) method is
established to define fuzzy items in the framework of fuzzy decision tree induction. The …

Low-resource languages are challenging to process intelligent decision systems due to
limited data and resources. As an effective way of processing low-resource languages in …

Rule-based models have become a popular way to represent and analyze the main
knowledge residing in data because of the increasing complexity and uncertainty. For …

Fuzzy rule-based models are widely employed to tackle regression problems due to their
simplicity and comprehensibility. Numeric functions (eg, linear ones) are generally utilized to …

With the development of different kinds of techniques, especially the Internet of Things (IoT),
a large amount of quantitative (either numeric or categorical) data have been generated …

Abstract Fuzzy C-Means (FCM) clustering algorithm is a popular unsupervised learning
approach that has been extensively utilized in various domains. However, in this study, we …

Network security is becoming increasingly important as computer technology advances. One
of the most important components in maintaining a secure network is an Intrusion Detection …