In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

Evolutionary Computation (EC) approaches are inspired by nature and solve optimization
problems in a stochastic manner. They can offer a reliable and effective approach to address …

Energy storage technology plays a role in improving new energy consumption capacities,
ensuring the stable and economic operation of power systems, and promoting the …

Artificial Neural Network (ANN) design is a complex task because its performance depends
on the architecture, the selected transfer function, and the learning algorithm used to train …

In this paper, we propose a novel technique for the automatic design of Artificial Neural
Networks (ANNs) by evolving to the optimal network configuration (s) within an architecture …

Artificial neural network (ANN) introduces different types of neural network structures and
has been applied successfully in diverse domains of real-world problems. Among various …

In neural networks, finding optimal values for the number of hidden neurons and connection
weights simultaneously is considered a challenging task. This is because altering the …

Multilayer perceptron (MLP)(trained with back propagation learning algorithm) takes large
computational time. The complexity of the network increases as the number of layers and …

The most pressing issue in network security is the establishment of an approach that is
capable of detecting violations in computer systems and networks. There have been several …

Conventional artificial neural network (ANN) learning algorithms for classification tasks,
either derivative-based optimization algorithms or derivative-free optimization algorithms …