A Decision-Making Model with Cloud Model, Z-Numbers, and Interval-Valued Linguistic Neutrosophic Sets.

Interval-valued linguistic neutrosophic sets (IVLNSs), Z-numbers, and the trapezium cloud model are powerful tools for expressing uncertainty and randomness. This paper aims to combine these methodologies. First, we review relevant concepts and operators, introducing a novel combination of IVLNSs and Z-numbers, which establishes a new form of expression.

Robust Support Vector Data Description with Truncated Loss Function for Outliers Depression.

Support vector data description (SVDD) is widely regarded as an effective technique for addressing anomaly detection problems. However, its performance can significantly deteriorate when the training data are affected by outliers or mislabeled observations. This study introduces a universal truncated loss function framework into the SVDD model to enhance its robustness and employs the fast alternating direction method of multipliers (ADMM) algorithm to solve various truncated loss functions.

Standoff tracking of a ground target based on coordinated turning guidance law.

Target tracking is a typical application of unmanned aerial vehicles(UAVs). However, it is difficult for the existing guidance laws to meet the requirements of convergence speed and tracking accuracy at the same time. A new guidance law based on a coordinated turning equation is proposed to achieve target tracking, and its asymptotic stability is proved.