Abstract Multi-Source Information Fusion (MSIF) is a comprehensive and interdisciplinary
subject, and is referred to as, multi-sensor information fusion which was originated in the …

Interval-valued data describe the random phenomenon that abounds in the real world, a
pivotal research orientation in uncertainty processing. With the rapid development of big …

Multisource information fusion is an important big data technology that plays a crucial role in
the fields of data mining and knowledge discovery. Multigranulation information fusion is an …

Early intervention and prevention of chronic diseases is a fundamental way to reduce
disease incidence. Due to the complex pathogenic factors of disease, the assessment of …

Abstract Information fusion technology plays a crucial role in integrating data from multiple
sources or sensors to generate comprehensive representation, which can eliminate …

The theory of three-way decisions, as a powerful methodology of granular computing, has
been widely used in making decision under uncertainty environments. Decision tasks in …

The data collected from the real world are diverse and include categorical data, numerical
data, incomplete data and noisy data. In addition, many real data sets may dynamically vary …

Feature selection is an important strategy for knowledge reduction in rough set. Interval-
valued data, as an extension of single values, can better express uncertain information from …

The medical big data of combined Chinese and western medicine diagnosis and treatment
(CCWMDT) is difficult to be used effectively in clinical medical decision-making because of …

With the rapid development of Big Data era, it is necessary to extract necessary information
from a large amount of information. Single-source information systems are often affected by …