Pomegranate seed oil (PSO), which is the major source of conjugated linolenic acids such as punicic acid (PuA), exhibits strong anti-inflammatory properties. Necrotizing enterocolitis (NEC) is a devastating disease associated with severe and excessive intestinal inflammation. The aim of this study was to evaluate the effects of orally administered PSO on the development of NEC, intestinal epith...

This paper proposes an improved version of particle swarm optimization (PSO) algorithm for the training of a neural network (NN). An architecture for the NN trained by PSO (standard PSO, improved PSO) is also introduced. This architecture has a data preprocessing mechanism which consists of a normalization module and a data-shuffling module. Experimental results showed that the NN trained by im...

This is a review paper. Review is carried out in three parts. First part covered up the introduction to PSO algorithm, load balancing based on PSO and multi objective job shop scheduling by improved PSO. Second part of this paper focused on workflow scheduling in cloud based on various versions of PSO. Third part explained PSO with cloud model with a little result analysis. This survey is done ...

The Particle Swarm Optimiser (PSO) is a population based stochastic optimisation algorithm, empirically shown to be efficient and robust. This paper provides a proof to show that the original PSO does not have guaranteed convergence to a local optimum. A flaw in the original PSO is identified which causes stagnation of the swarm. Correction of this flaw results in a PSO algorithm with guarantee...

This paper presents a method for data model partitioning of power distribution network. Modern Distribution Management Systems which utilize multiprocessor systems for efficient processing of large data model are considered. The data model partitioning is carried out for parallelization of analytical power calculations. The proposed algorithms (Particle Swarm Optimization (PSO) and distributed ...

For the analysis of the paramagnetic spin orbit (PSO) term of the NMR spin–spin coupling constant (SSCC), ring current density and PSO density distribution are derived and used to explain magnitude and sign of the isotropic PSO term. Decomposition of the PSO components into orbital contributions helps to identify those orbital pairs (occupied, virtual) dominating the PSO term. The induction of ...

-Aiming at the shortcoming of basic PSO algorithm, that is, easily trapping into local minimum, we propose an advanced PSO algorithm with SA and apply this new algorithm for solving TSP problem. The core of algorithm is based on the PSO algorithm. SA method is used to slow down the degeneration of the PSO swarm and increase the swarm’s diversity. The comparative experiments were made between PS...

Niching as an important technique for multimodal optimization has been used widely in the Evolutionary Computation research community. This chapter aims to provide a survey of some recent efforts in developing stateof-the-art PSO niching algorithms. The chapter first discusses some common issues and difficulties faced when using niching methods, then describe several existing PSO niching algori...

A new model for evolving the structure of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. The model is a hybrid technique that combines a Genetic Algorithm (GA) and a PSO algorithm. Each GA chromosome is an array encoding a meaning for updating the particles of the PSO algorithm. The evolved PSO algorithm is compared to a human-designed PSO algorithm by using ten artifi...

Particle swarm optimization (PSO) has shown its good search ability in many optimization problems. However, PSO often easily fall into local minima because the particles could quickly converge to a position by the attraction of the best particles. Under this circumstance, all the particles could hardly be improved. This paper presents a hybrid PSO, namely LSPSO, to solve this problem by employi...