Optimization Design of Gravity Dam Section Based on PSO Algorithm

Liang Ming Hu; Yi Zhi Li

doi:10.4028/www.scientific.net/AMR.424-425.535

Paper Titles

Structure Optimization of Large-Diameter Percussive Drill
p.516

Analysis of Soft Rock Tunnel Mechanics Effects Based on Strain Softening Model of Surrounding Rock
p.520

Simulation of Design and Optimization of Local Oil Gas Ventilation Equipments with CFX
p.526

Analysis of Influencing Factors of Coal-Biomass Compound Briquets Combustion Characteristics
p.531

Optimization Design of Gravity Dam Section Based on PSO Algorithm
p.535

The Process Modification of Bathing Wastewater Treatment and Reuse System in School
p.540

Application of Organic Inclusion in Hydrocarbon Exploration
p.545

Design and Implementation of NIDS String Matching Based on SOPC
p.551

Analysis of Heat Exchange Efficiency during the Spray Cooling Process
p.555

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 424-425Optimization Design of Gravity Dam Section Based...

Optimization Design of Gravity Dam Section Based on PSO Algorithm

Abstract:

Particle Swarm Optimization (PSO) algorithm is a technique for optimization based on iteration, which initializes system to product a series of random solutions, in this solution space, particles commit themselves to search for a better solution and in the final the optimal one is found. Applying this algorithm to the design of gravity dam section then we find: PSO, as shown by the example given in this paper, is an available algorithm which is not only tally with the actual situation, but safe and economical. So, PSO provides a new idea and method for optimization design of gravity dam section.

You might also be interested in these eBooks

Advanced Research on Engineering Materials, Energy, Management and Control

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 424-425)

Pages:

535-539

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.424-425.535

Citation:

Cite this paper

Online since:

January 2012

Authors:

Liang Ming Hu, Yi Zhi Li

Keywords:

Constraint Condition, Gravity Dam, Optimization Design, Particle Swarm Optimization (PSO), Section

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] J. Kennedy, R.C. Eberhart: Particle swarm optimization. In: IEEE International Conference on Neural Networks, Perth, Australia, IEEE Service Center, Piscataway, NJ, pp.1942-1950. (1995).

Google Scholar

[2] Eberhart, R .C. Kennedy J.: A new optimizer using particles swarm theory. In: Sixth International on Micro Machine and Human Science. Nagoya, Japan, (1995).

DOI: 10.1109/mhs.1995.494215

Google Scholar

[3] Y.F. Shi, R.C. Eberhart: A modiﬁed particle swarm optimizer. In: IEEE International Conference on Evolutionary Computation, pp.69-72. (1998).

Google Scholar

[4] Liu Bo: PSO algorithm and its engineering application. Publishing House of Electronics Industry, Beijing (2010).

Google Scholar

[5] Li Zhi, Zheng Xiao: Application of improved particle swarm algorithm in optimization of agricultural engineering, edtied by Transactions of the Chinese Society of Agricultural Engineering, pp.15-17. China, (2004).

Google Scholar

[6] Li Zhi, Zheng Xiao: Application of improved particle swarm algorithm in optimization of agricultural engineering. In: Transactions of the Chinese Society of Agricultural Engineering, pp.15-18. China, (2004).

Google Scholar

[7] Hu Liangming, Chen Feng and Li Yizhi: Research of optimal design for gravity dam based on niche genetic algorithm. In: IEEE International Conference on Computer Education, Simulation and Modeling, pp.327-328. Springer, Wuhan (2011).

DOI: 10.1007/978-3-642-21802-6_52

Google Scholar

[8] Lin Jiyong: Hydraulic structure. China WaterPower Press, Beijing, China (2006).

Google Scholar