Heuristic optimization algorithms are suitable for a variety of optimization problems, and more easily extended to large-scale optimization problems. The firefly algorithm is inspired by the ...

The challenge of navigating unmanned aerial vehicles (UAVs) can be effectively tackled through the application of reinforcement learning (RL) methodologies. Nonetheless, the baseline Proximal Policy ...

Therefore, meta-heuristic optimization algorithms are widely utilized to find the parameters of support vector regression for short-term electric loads. Peng et al. (2016) presented a support vector ...

The automatic fitting of spiking neuron models to experimental data is a challenging problem. The integrate and fire model and Hodgkin–Huxley (HH) models represent the two complexity extremes of ...