Feature selection has been considered as an effective method to solve imbalanced
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …

This work investigates an unmanned aerial vehicle (UAV) assisted IoT system, where a UAV
flies to each foothold to collect data from IoT devices, and then return to its start point. For …

To improve the tracking accuracy of moving targets in Non-Line-of-Sight (NLOS)
environments and reduce positioning errors, a hybrid TDOA/AOA positioning method is …

Some recent research reveals that a topological structure in meta-heuristic algorithms can
effectively enhance the interaction of population, and thus improve their performances …

Partial shading (PS) is a prevalent phenomenon that often affects photovoltaic (PV)
installations, leads to the appearance of numerous peaks in the power-voltage …

A dandelion algorithm (DA) is a recently developed intelligent optimization algorithm for
function optimization problems. Many of its parameters need to be set by experience in DA …

As a novel neural network-based learning framework, a broad learning system (BLS) has
attracted much attention due to its excellent performance on regression and balanced …

Feature selection (FS) is an important data preprocessing technology for machine learning
and data mining. Metaheuristic algorithm (MH) has been widely used in feature selection …

In an intelligent transportation system, accurate traffic flow prediction can provide significant
help for travel planning. Even though some methods are proposed to do so, they focus on …

In recent years, swarm intelligence optimization methods have been increasingly applied in
many fields such as mechanical design, microgrid scheduling, drone technology, neural …