Source mask optimization (SMO) is an effective method for improving the image quality of high-node lithography. Reasonable algorithm critical issue in SMO. A GA-APSO hybrid algorithm, combining genetic (GA) and adaptive particle swarm (APSO), was proposed to inversely obtain global optimal distribution pixelated source lithographic imaging process. The computational efficiency improved by GA PS...

Here, a novel hybrid method of intelligent fault identification within complex mechanical systems was proposed using parallel-factor (PARAFAC) theory and adaptive particle swarm optimization (APSO) for support vector machine (SVM). The multi-scale analysis studied to reconstruct tensor feature information based on three-dimensional matrix time, frequency, spatial vectors. A wavelet used transfo...

The infrastructure build in the big data platform is reliable to challenge the commercial and noncommercial IT development communities of data streams in high dimensional data cluster modeling. The APSO ie., Accelerated Particle Swarm Optimization is a technique which commonly known for data's are sourced to accumulate their continuation in the batch model induction algorithms which is not feas...

Optimization algorithms are very important for the Optimal Power Flow (OPF). They could be divided into two classes: traditional local search methods and heuristic global ones. Interior point (IP) algorithm has been known as one of the most prominent and fastest method, but its local exploitation characteristic leads to the fact that it could be easily trapped by local optimum. However, heurist...

This paper presents swarm intelligence based Adaptive Particle Swarm Optimization (APSO) technique to determine optimum design of Switched Reluctance Machine (SRM). In APSO technique, the inertia weight factor is made adaptive on the basis of objective functions of the current and best solutions to avoid premature convergence. The SRM design is treated as nonlinear multivariable constrained opt...

In this paper, we presented the performance of forecasting model and error correction will affect the accuracy of short-term load forecasting. Least squares support vector machines (LS-SVM) based on improved particle swarm optimization is selected as load forecasting model. Forecasting accuracy and generalization performance of LS-SVM depend on selection of its parameters greatly. Adaptive part...

In recent years, evolutionary optimization (EO) techniques have attracted considerable attention in the design of electromagnetic systems of increasing complexity. This paper presents a comparison between two optimization algorithms for the synthesis of uniform linear and planar antennas arrays, the first one is an adaptive particle swarm optimization (APSO) where the inertia weight and acceler...

In this paper, we have proposed adaptive methods for image restoration in which the input images are affected by noise which is removed by fuzzy based median filter (FMF). The noise removed images from the FMF is appears to be so there is a need to restore the images with high quality. To restore the images an APSO (Adaptive particle swarm optimization) based Richardson-Lucy (R-L) algorithm is ...