Large-scale optimization problems (LSOPs) become increasingly ubiquitous but
complicated in real-world scenarios. Confronted with such sophisticated optimization …

This paper proposes a novel gradient-boosting-based ensemble system with a fuzzy
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …

In recent years, both machine learning and computer vision have seen growth in the use of
multi-label categorization. SMOTE is now being utilized in existing research for data …

Existing research mainly uses prior knowledge to set all fuzzy sets in a fuzzy system to the
same type. In data-driven fuzzy modeling, automatically determining the type of fuzzy set is …

Particle swarm optimization (PSO) is a well-known optimization method used for solving
various optimization problems. However, PSO suffers from premature convergence and is …

The tracker based on correlation filter shows excellent performance in tracking accuracy and
running speed. However, the models of correlated filter trackers are always updated with …

In this paper, a new two-dimensional gaussian hierarchical priority fuzzy system (TGHPFS)
is proposed to handle interval-valued data. TGHPFS first performs hierarchical clustering of …

In order to overcome the influence of model uncertainty and external disturbance on the
trajectory tracking accuracy of four-wheel omnidirectional mobile robot (FM-OMR), a new …

Seldom existing studies directly focus on the control issues of 2-D spatial partial differential
equation (PDE) systems, although they have strong application backgrounds in production …

In this paper, a novel self-learning design of an interval type-2 hierarchical fuzzy system (IT2
HFS) based on rule relevance is proposed. Different from the existing methods, this paper …