The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …

Particle swarm optimization (PSO) has undergone many changes since its introduction in
1995. As researchers have learned about the technique, they have derived new versions …

The learning process of artificial neural networks is considered as one of the most difficult
challenges in machine learning and has attracted many researchers recently. The main …

We have developed a software package CALYPSO (Crystal structure AnaLYsis by Particle
Swarm Optimization) to predict the energetically stable/metastable crystal structures of …

As a powerful tool for data regression and classification, neural networks have received
considerable attention from researchers in fields such as machine learning, statistics …

One of the main concerns in geotechnical engineering is slope stability prediction during the
earthquake. In this study, two intelligent systems namely artificial neural network (ANN) and …

Particle swarm optimization (PSO) has shown to be an efficient, robust and simple
optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical …

Abstract The Multi-Layer Perceptron (MLP), as one of the most-widely used Neural Networks
(NNs), has been applied to many practical problems. The MLP requires training on specific …

Due to the variability of the radiated signal of the underwater targets, the classification of the
underwater acoustical dataset is a challenging problem in the real world application. In this …

An evolutionary recurrent network which automates the design of recurrent neural/fuzzy
networks using a new evolutionary learning algorithm is proposed in this paper. This new …