The traditional unidirectional, passive distribution power grids are rapidly developing into
bidirectional, interactive, multi-coordinated smart grids that cover distributed power …

Coarse-grained force fields (CG FFs) such as the Martini model entail a predefined, fixed set
of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded …

Particle swarm optimization (PSO) is a popular metaheuristic for deterministic optimization.
Originated in the interpretations of the movement of individuals in a bird flock or fish school …

Particle swarm optimization (PSO) is a population-based algorithm designed to tackle
various optimization problems. However, its performance deteriorates significantly when …

Particle swarm optimization (PSO) is a population-based optimization technique that has
been applied extensively to a wide range of engineering problems. This paper proposes a …

This study briefly reviews the application of Genetic Algorithm (GA) and Particle Swarm
Optimization (PSO) in geotechnical engineering since GA and PSO are widely used in civil …

We propose a new particle swarm optimization algorithm for problems where objective
functions are subject to zero-mean, independent, and identically distributed stochastic noise …

Extreme hydrological events induced by typhoons in reservoir areas have presented severe
challenges to the safe operation of hydraulic structures. Based on analysis of the seepage …

A novel method named probabilistic multimodal optimization (PMO) algorithm is proposed in
this paper to competently optimize noisy objective function. In the PMO algorithm, we …

Particle Swarm Optimization (PSO) is a population-based algorithm designed to tackle
various optimization problems. However, its performance deteriorates significantly when …