In the field of optimization problems, the optimization of energy systems problems is of
significant importance, mainly due to their dramatic role in achieving sustainability. The …

A very recent methodology of data sampling with a sub-Nyquist rate is compressive sensing
(CS). CS theory is established based on the higher sparsity of the data containing …

This paper focuses on develo** a computationally economic lightweight artificial
intelligence (AI) technology for smartphones. Until date, no commercial system is available …

This paper proposes an improved binary bat algorithm (IBBA) for solving static and dynamic
transmission network expansion planning (TNEP) problems for standard and realistic …

This study presented a new multi-species binary coded algorithm, Mendelian evolutionary
theory optimization (METO), inspired by the plant genetics. This framework mainly consists …

The transmission network expansion planning (TNEP) problem consists of determining the
necessary infrastructure additions, within a planning horizon, to minimize an investment …

This chapter analytically compares the efficiency of the recent plant biology-inspired genetic
algorithm (PBGA) and the firefly algorithm (FA) optimizer. The comparison is over a range of …

The sailfish optimizer (SFO) is a new metaheuristic swarm intelligence optimization
algorithm based on the hunting behavior of biological groups, simulating the elite strategy of …

In order to accommodate the uncertainty and variability of wind power, this paper proposes a
scenario-based probabilistic model to assess the impact of intermittent wind power-based …

Artificial neural networks (ANN) have a great impact on research in the field of artificial
intelligence. It has great capability besides the easy implementation, and due to that, it has …