In fuzzy information granule (FIG) based short-term forecasting models, the constructed FIG
focuses on one of two tasks: capture data characteristic and improve semantic description at …

The advent of big data related to spatial position knowledge, called geospatial big data,
provides us with opportunities to recognize the urban environment. Existing database …

Clustering is one of the essential branches of data mining, which has numerous practical
uses in real-time applications. The Kernel K-means method (KK-means) is an extended …

Cluster validity indices (CVIs) for evaluating the result of the optimal number of clusters are
critical measures in clustering problems. Most CVIs are designed for typical data-type …

Federated learning (FL) belongs to distributed machine learning. It allows data information
sharing between users while protecting their data privacy at the same time. However, in …

In the existing short-term forecasting methods of time series, two challenges are faced:
capture the associations of data and avoid cumulative errors. For tackling these challenges …

Statistical modeling plays a critical role in various scientific fields as it offers an
understanding of how the response variable of interest is linked to a range of explanatory …

This paper presents a biased random-key genetic algorithm for k-medoids clustering
problem. A novel heuristic operator was implemented and combined with a parallelized …

Indonesia's frequent earthquakes, caused by its position at the convergence of multiple
tectonic plates, Indonesia's frequent earthquakes, caused by its position at the convergence …

Uncertain data, where each feature is represented by probability density functions instead of
fixed values, have been widely used in diverse applications such as sensor networks …