Due to the multilayer nature of real-world systems, the problem of inferring multilayer
network structures from nonlinear and complex dynamical systems is prominent in many …

In real-world applications, there exist multiple fuzzy cognitive maps (FCMs) learning tasks
with similar attributes that have to be optimized simultaneously, however, all existing …

The problem of reconstructing nonlinear and complex dynamical systems from available
data or time series is prominent in many fields, including engineering, physical, computer …

Preeclampsia (PE) is a heterogeneous disease that seriously affects the health of mothers
and fetuses. Lack of detection assays, its diagnosis and intervention are often delayed when …

The problem of inferring nonlinear and complex dynamical systems from available data is
prominent in many fields, including engineering, biological, social, physical, and computer …

Reconstructing the interacting structure of complex networks from available data is
fundamental to understanding and controlling its collective dynamics. From the perspective …

With technological breakthroughs, drone deliveries have become increasingly popular,
especially during the COVID-19 pandemic. Driven by both economical benefit and …

Reconstructing the structure of complex networks from time series is beneficial to
understanding and controlling the collective dynamics of networked systems. Existing …

Evolutionary computation and complex networks have received considerable attention in
recent years. Inspired by natural selection and evolutionary theory, evolutionary algorithms …

Reconstructing complex network structures from measurable data has become a central
issue in contemporary network science and engineering. In this paper, we tackle the …