Data clustering is one of the most popular techniques in data mining. It is a process of
partitioning an unlabeled dataset into groups, where each group contains objects which are …

A new nature-inspired optimization method, named the Golden Jackal Optimization (GJO)
algorithm is proposed, which aims to provide an alternative optimization method for solving …

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas
individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This …

Particle swarm optimization (PSO) is a population based meta-heuristic search algorithm
that has been widely applied to a variety of problems since its advent. In PSO, the inertial …

The growing costs of fuel and operation of power generating units warrant improvement of
optimization methodologies for economic dispatch (ED) problems. The practical ED …

The shape optimization of complex curves is a crucial and intractable technique in computer
aided geometric design and widely used in many product design and manufacturing fields …

Strategic planning for optimal operation of modern power systems has always been a
significant task to satisfy the techno‐social aspects in the sustainable energy scenario. In the …

In this study, we propose an improved version of the adaptive neuro-fuzzy inference system
(ANFIS) for forecasting the air quality index in Wuhan City, China. We propose a hybrid …

This article presents a two-timescale duplex neurodynamic approach to mixed-integer
optimization, based on a biconvex optimization problem reformulation with additional …

A global parameter estimation method for a permanent magnet synchronous machines
(PMSM) drive system is proposed, where the electrical parameters, mechanical parameters …