Application of Hybrid Genetic Algorithm in Control Network Adjustment

Wei Chen

doi:10.4028/www.scientific.net/AMM.353-356.3434

Paper Titles

Program Design of Leveling-Network Conditional Adjustment Based on Transferring Matrix
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The Application of the TM30 Measuring Robot in the Open Pit Slope Monitoring
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Accuracy Assessment of Nonlinear Least Squares Adjustment Parameters
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Application of Hybrid Genetic Algorithm in Control Network Adjustment
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A Regional Zenith Tropospheric Correction Model Based on the Guangxi CORS Network
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The Understanding, Definition, Redress and Application Based on the Figure Symbol “∞” of Probability Theory
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Ambiguity Resolution with Single Epoch for GNSS Reference Network Based on Atmospheric Delay Information
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Analytical Solution of Linear Intersection Based on Jacobi Algorithm and its Comparison with Least Squares Solution
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 353-356Application of Hybrid Genetic Algorithm in Control...

Application of Hybrid Genetic Algorithm in Control Network Adjustment

Abstract:

In this paper a hybrid genetic algorithm which consists of the simplex method and the genetic algorithm is proposed for the defect of poor local search ability of genetic algorithm. The hybrid genetic algorithm has the advantages of good global convergence of the genetic algorithm and excellent local search ablility of the simplex method and can improve search speed and calculation accuracy.The hybrid algorithm is applied to the control network adjustment and experimental results demonstrates the effectiveness and superiority of the algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 353-356)

Pages:

3434-3437

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.353-356.3434

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Online since:

August 2013

Authors:

Wei Chen

Keywords:

Genetic Algorithm (GA), Measurement Adjustment, Simplex Method

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References

[1] Xinzhou Wang. Theory and application of nonlinear model parameter estimation [M] (In Chinese). Wuhan: Wuhan University Press（2002）.

Google Scholar

[2] D Venkatesan, K Kannan, R Saravanan: Neural Comput & Applic, Vol. 18 (2009), p.135–140.

Google Scholar

[3] Srinivas M, Patnaik L M: IEEE Trans Systems Man and Cybernetics, Vol. 4(1994), p.656～667.

Google Scholar

[4] M Nakamura Beatrice, M Ombuki, K Shimabukuro, K Onaga: Artif Life Robotics, Vol. 2 (1998), pp.74-79.

Google Scholar

[5] Survey Adjustment subject groups: Surveying Adjustment Foundation(3) [M](in Chinese). Wuhan: Wuhan University of Science and Technology of Surveying and Mapping Press（1999）.

Google Scholar