This paper proposes a multi-threshold image segmentation method based on improved
emperor penguin optimization (EPO). The calculation complexity of multi-thresholds …

This paper proposes a modified marine predators algorithm based on quantum theory to
handle the multilevel image segmentation problem. The main aims of using quantum theory …

Neighborhood-based attribute reduction plays a vital role in pattern recognition, for selecting
a series of informative and relevant attributes from data sets. The increase in dimensionality …

The satellite power system is one of the core systems to ensure the normal on-orbit
operation of satellite, and is also a representative of typical complex nonlinear systems …

Abstract Machine learning algorithms treat credit risk prediction as a binary classification
problem. However, two-way decisions with a single threshold force to make either a default …

Decision-theoretic rough sets (DTRSs), which can be considered as generalized rough set
models produced by Bayesian risk minimum and three-way decisions (3WD) theories, have …

Crime linkage is a difficult task and is of great significance to maintaining social security. It
can be treated as a binary classification problem. Some crimes are difficult to determine …

There are some problems in the shifting process of hydraulic CVT, such as irregularity, low
stability and high failure rate. In this paper, the BP neural network and convolutional neural …

For a completely distributive De Morgan algebra L, we develop a general framework of L-
fuzzy rough sets. Said precisely, we introduce a pair of L-fuzzy approximation operators …

The notion of neighborhood systems is abstracted from the geometric notion of “near,” and it
is primitive in the theory of topological spaces. Now, the notion of neighborhood systems has …