The increase in energy demand has made the renewable resources more attractive.
Representing the largest sources of renewable energy, solar and wind systems are …

The digital transformation of the energy sector toward the Smart Grid paradigm, intelligent
energy management, and distributed energy integration poses new requirements for …

Many problems in science and engineering can be formulated as optimization problems,
subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually …

The behavior of natural phenomena has become one of the most popular sources for
researchers to design optimization algorithms for scientific, computing and engineering …

In order to carry out the evaluation, control and maximum power point tracking on
photovoltaic (PV) systems, accurate and reliable model parameter identification of PV cell …

Cloud computing represents relatively new paradigm of utilizing remote computing
resources and is becoming increasingly important and popular technology, that supports on …

Nowadays, the use of metaheuristic algorithms has dramatically increased in order to
achieve the optimal solution in solving continuous optimization problems. In this paper, a …

In this study, we developed multiple hybrid machine-learning models to address parameter
optimization limitations and enhance the spatial prediction of landslide susceptibility models …

This paper describes the flight path planning for unmanned aerial vehicles (UAVs) based on
the advanced swarm optimization algorithm of the bat algorithm (BA) in a static environment …

Grey wolf optimizer (GWO) algorithm is a relatively novel population-based optimization
technique that has the advantage of less control parameters, strong global optimization …