With the growth of deep learning in various classification problems, many researchers have
used deep learning methods in environmental sound classification tasks. This paper …

Background: The Multi Depot Pickup and Delivery Problem with Time Windows and
Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing …

Adaptive parameter control is critical in the design and application of evolutionary algorithm
(EA), so does in differential evolution. In the past decade, many adaptive evolutionary …

Many state-of-the-art evolutionary algorithms (EAs) can be categorized as sequential hybrid
EAs, in which various EAs are sequentially executed. The timing to switch from one EA to …

Heterogeneous vehicles (eg, unmanned ground vehicle (UGV) and unmanned aerial
vehicle (UAV)) are best suited for surveillance application over large areas. UAVs are fast …

Depressive Disorder (DD) is a leading cause of disability worldwide. Screening tools for
detecting DD symptoms are essential for monitoring and efficient managing. Remarkably …

The performance of evolutionary algorithms (EAs) is strongly affected by their configurations.
Thus, algorithm configuration (AC) problem, that is, to properly set algorithm's configuration …

Electrical capacitance tomography excels in measuring multiphase flows, but it faces
challenges in reconstructing high-accuracy images. To tap into the potential of this …

Distributed file systems are widely used nowadays, yet using their default configurations is
often not optimal. At the same time, tuning configuration parameters is typically challenging …

The performance of an evolutionary algorithm (EA) is deeply affected by its control
parameter's setting. It has become a trend in recent studies to treat the control parameter as …