Due to many classical identification methods cannot be directly used for closed-loop control system, an improved identification method is proposed to simultaneously identify model parameters and the structure. The improved identification method used the genetic algorithm to estimate the initial search scope for the PSO algorithm, and then used the search result as the initial value of the Rosen...

This paper presents a Particle Swarm Optimization with Improved Inertia Wight (PSO-IIW) for Combined Heat and Power Economic Dispatch (CHPED) problem. The proposed PSO-IIW technique, which is a population based global search and optimization technique, has been developed to solve the CHPED problem. The CHPED problem is formulated as an optimization problem which is solved by the PSO-IIW techniq...

To compensate the flaws of single neural network such as low classification precision and long training time as well as weak generalized ability etc, the paper proposes a novel ensemble neural classifier for stream turbine vibration fault diagnosis with improved PSO-based. The method fully utilizes the advantages of PSO, such as fast seeking speed and easily realizing mode etc, the integrated t...

The optimal design of planar multilayered electromagnetic wave absorbers is presented. The optimization process is based on an improved particle swarm optimization (PSO). Assumed that the number of layers is given, in order to obtain an ideal absorber which is thin and has a low reflection coefficient within a wide band of frequencies, the thickness of each layer needs to be optimized as well t...

This article proposes an improved particle swarm optimization (PSO) with suggested parameter setting “Selective Particle Regeneration”. To evaluate its reliability and efficiency, this approach is applied to multimodal function optimizing tasks. 12 benchmark functions were tested, and results are compared with those of PSO and GA-PSO. It shows the proposed method is both robust and suitable for...

In this paper, we propose a Particle Swarm Optimization (PSO) based solution to the Orienteering Problem. A major problem in many PSO applications is the premature convergence of some particles to local optimums. To overcome this problem in our application, such particles are re-initiated; consequently, the exploration capability of PSO is improved. Furthermore, by employing Reduced Variable Ne...

Considering the standard particle swarm optimization (PSO) has the shortcomings of low convergence precision in job shop scheduling problems, the job shop scheduling solution is presented based on improved particle swarm optimization (A-PSO). In this paper, the basic theory of A-PSO is described. Also, the coding and the selection of parameters as well as the decoding of A-PSO are studied. It u...

Data clustering is a powerful technique for discerning the structure of and simplifying the complexity of large scale data. An improved technique combining chaotic map particle swarm optimization (CPSO) with an acceleration strategy, is proposed in this paper. Accelerated chaotic particle swarm optimization (ACPSO) searches for cluster centers of an arbitrary data set and can effectively find t...

This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called particle swarm optimization with mutation operators (PSOM). The mutation operators are ...

The magnetotelluric (MT) method has become more widely used in hydrocarbon exploration. The inversion of MT data, which can determine the electrical structure of subsurface, is a nonlinear and multimodal optimization problem. Particle swarm optimization(PSO) algorithm is a good solver for this geophysical inversion problem, whereas it has a shortage of heavy computation time. An improved parall...