Despite the rapid progress of neuromorphic computing, inadequate capacity and insufficient
representation power of spiking neural networks (SNNs) severely restrict their application …

Typically, industrial processes possess both temporal and spatial dependencies due to
intravariable dynamics and intervariable couplings. The two dependencies have different …

Precise actuation is a widely utilized technology in the realm of high-end equipment.
Piezoelectric actuators (PEAs) stand out due to their exceptional attributes, including high …

This paper presents a comprehensive general overview of the extensive literature available
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …

Fuzzy neural network (FNN) is a structured learning technique that has been successfully
adopted in nonlinear system modeling. However, since there exist uncertain external …

In clustering fields, the deep graph models generally utilize the graph neural network to
extract the deep embeddings and aggregate them according to the data structure. The …

An optimal tracking control problem for a class of nonlinear systems with guaranteed
performance and asymmetric input constraints is discussed in this paper. The control policy …

Accurate matching between user and candidate news plays a fundamental role in news
recommendation. Most existing studies capture fine-grained user interests through effective …

Granular-ball support vector machine (GBSVM) is a significant attempt to construct a
classifier using the coarse-to-fine granularity of a granular ball as input, rather than a single …

Since precisely sensing the underwater environment is a challenging prerequisite for safe
and reliable underwater operation, interest in underwater image processing is growing at a …