Application Research on Improved Fusion Algorithm Based on BP Neural Network and POS

Hong Li; Xue Ding

doi:10.4028/www.scientific.net/AMM.733.898

Paper Titles

Surrogating for High Dimensional Computationally Expensive Multi-Modal Functions with Elliptical Basis Function Models
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Study on Approximation Methods with Chebyshev Polynomial Models
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Extraction of Inertial Parameters Based on 3D-Voxel Model of Equal Volume
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Application of the Combination Prediction Model in Forecasting the Short-Term Wind Power
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Application Research on Improved Fusion Algorithm Based on BP Neural Network and POS
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Group Synchronization Analysis of Network by Matrix Theory
p.902

Harmonic Analysis Based on Modified Hyperbolic S-Transform
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Statistical Inference and Application for Partially Linear Models
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Analysis of Extreme High-Temperature Time Series Based on Empirical Mode Decomposition
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 733Application Research on Improved Fusion Algorithm...

Application Research on Improved Fusion Algorithm Based on BP Neural Network and POS

Abstract:

Optimization problem is the problem which can be often encountered mostly in industrial design, and the key of optimization is to find the global optimum and higher constriction speed. This paper proposes a PSO algorithm based on BP neural network by neural network trains and selects individual extreme best randomly, to make the particle follow the optimal particle in the solution space search, and obtain the optimum extreme best in the whole situation. Through the application of the simulation experiment on image segmentation showed that the algorithm is suitable in dealing with multiple types function and constraint, with fast convergence speed, and easy combination with traditional optimization methods, thus improving its own limitations, and solving problems more efficiently.

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Periodical:

Applied Mechanics and Materials (Volume 733)

Pages:

898-901

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.733.898

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Online since:

February 2015

Authors:

Hong Li*, Xue Ding

Keywords:

Application Research, BP Neural Network, Improved Fusion Algorithm, Particle Swarm Optimization

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References

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