Diversion System Scenarios Optimization Considering Indicators Correlation

Abstract:

The decision-making indicators of hydropower engineering diversion scenario are always related with diversion risk, and for determining the optimal scenario, correlation analysis and decoupling for indicators is the key problem. Using k-additive fuzzy measure to characterize and decouple the relevance of indicators on the base of the analysis and quantization of indicators, and determining the weights of indicators according to maximum fuzzy measure entropy principle, finally the synthetic appraisal value for diversion scenarios can be calculated with choquet integral to rank and select optimal scenario. The case study shows that the decision-making method is effective for characterizing and decoupling the relevance of the indicators and enhancing the decision-making veracity to provide an effective method for the diversion scenario decision of hydropower engineering.

• Periodical: Advanced Materials Research (Volumes 1065-1069)
• Pages: 2554-2560
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1065-1069.2554
• Online since: December 2014
• Authors: Li Zhe Luo*, Xue Hong Yang, Wen Zhen Yu, Shao Hua Pan
• Keywords: Choquet Integral, Correlation Decoupling, Diversion System, K-Additive Fuzzy Measure, Risk Analysis

References

[1] Hu Z, Liu Q, He C, et al. Multi-objective Risk Model of Optimal River Diversion Standards During Initial Stage Construction for Hydroelectric Project[J]. 2001(08).

[2] Zhi-Gen H U, Xi-E F, Quan L, et al. Design of integrated risk distribution mechanism of construction diversion system[J]. Journal Of Hydraulic Engineering, 2006, 37(10): 1270-1277.

[3] Xi-E F, Zhi-Gen H U, Peng J. Integrated risk of construction diversion system based on the Monte-Carlo method[J]. Advances In Water Science, 2007, 18(4): 604-608.

[4] Fan X E, Hu Z, Liu Q. Multi-objective decision model for construction diversion scenarios based on utility[J]. Engineering Sciences, 2008(2).

[5] Zhong D, Jun P. Study on expert system for decision of the construction diversion scenarios [J]. 1995, 28(5): 687-690.

[6] Marichal J. Axiomatic approach of the discrete choquet integral as a tool to aggregate interacting criteria[J]. IEEE Transactions on Fuzzy Systems. 2000, 8(6): 800-807.

DOI: 10.1109/91.890347

[7] Yang S, Deng-Hua Z. Study on Construction Schedule Management and Control Method for Hydraulic & Hydropower Engineering Based on Visual Simulation[J]. Systems Engineering -Theory & Practice, 2006, 26(8): 55-62.

[8] Liu G, Jiang C. Incidence matrix based methods for computing repetitive vectors and siphons of petri net[J]. Journal of Information Science and Engineering. 2009, 25(1): 121-136.

[9] Jian-Zhang W U, Qiang Z. Multicriteria decision making method based on 2-order additive fuzzy measures[J]. Systems Engineering -Theory & Practice, 2010, 30(7): 1229-1237.

[10] Lee S, Ryu K H, Sohn G. Study on entropy and similarity measure for fuzzy set[J]. IEICE Transactions on Information and Systems. 2009, E92-D(9): 1783-1786.

DOI: 10.1587/transinf.e92.d.1783

[11] Lei Z, Zhi-Ping F, Qi Y. Assessing the Integrated Risk Based on Choquet Integral[J]. Journal Of Northeastern University (Natural science), 2010, 31(11): 1665-1668.

[12] Hu Z G, Liu Q, He C H, et al. Risk analysis of retaining rockfill cofferdam for diversion based on the Monte-Carlo method[J]. Advances In Water Science, 2002, 13(5): 634-638.