In this chapter, a Particle Swarm Optimization-Based Session Key Generation for wireless communication (PSOSKG) is proposed. This cryptographic technique is solely based on the behavior of the particle swarm. Here, particle and velocity vector are formed for generation of keystream by setting up the maximum dimension of each particle and velocity vector. Each particle position and probability v...

In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS)....

Reactive power optimization is important to ensure power quality, improve system security, and reduce active power loss. So, this paper proposed parallel immune particle swarm optimization (PIPSO) algorithm. This algorithm makes basic particle swarm optimization (BPSO) and discrete particle swarm optimization (DPSO) to optimize in parallel, and improves the convergence capability of particle sw...

clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. the aim of clustering is to collect data points. in this paper, a cultural algorithm (ca) is presented to optimize partition with n objects into k clusters. the ca is one of the effective methods for searching into the problem space in order to find a n...

shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. however, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. in order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (pso) algorithm. the ...

this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

The objective of this thesis is to investigate how to improve Particle Swarm Optimization by hybridization of stochastic search heuristics and by a Self-Organized Criticality extension. The thesis will describe two hybrid models extending Particle Swarm Optimization with two aspects from Evolutionary Algorithms, recombination via breeding and gene flow restriction via subpopulations. A further ...

This paper proposes a Particle Swarm Optimization (PSO) algorithm called HelixPSO for finding RNA secondary structures that have a low energy and are similar to the native structure. HelixPSO is compared to the recent algorithms RnaPredict, SARNA-Predict, SetPSO, and RNAfold. For a set of standard RNA test sequences it is shown that HelixPSO obtains a better average sensitivity than SARNA-Predi...

The Particle Swarm Optimization (PSO) was used to select the three best inputs to explain the input-output relationship of both 'defects' and 'time' models. A ranking-based system was used to select the best features. Using this system, the value of each particle in the swarm represents the importance of each feature. During optimization, the three best-ranked features were used to train the Mu...

The paper proposed a network scheduling in cloud computing based on intelligence Particle Swarm Optimization algorithm aimed at the disadvantages of cloud computing network scheduling. Firstly, on the basis of cloud model, used intelligence Particle Swarm Optimization algorithm with strong ability of global searching to find the better solution of cloud computing network scheduling then turned ...