Wet-Dry Classification of Annual Runoff Based on LBA-PP Model

MAO Zong-bo; DAO Hai-ya

doi:10.11988/ckyyb.20150635

PDF(1315 KB)

Journal of Changjiang River Scientific Research Institute ›› 2016, Vol. 33 ›› Issue (9) : 23-27. DOI: 10.11988/ckyyb.20150635

WATER RESOURCES AND ENVIRONMENT

Wet-Dry Classification of Annual Runoff Based on LBA-PP Model

MAO Zong-bo,DAO Hai-ya

Author information +

History +

Abstract

The wet-dry features of annual runoff depend on the size and time-history distribution characteristics of runoff itself.In view of this,we put forward a LBA-PP model of wet-dry classification of annual runoff by searching the optimum projection direction using bat algorithm (LBA) improved with a Lévy flight strategy in association with projection pursuit (PP) model.We also construct a particle swarm optimization (PSO) algorithm PP model for comparison,with the annual runoff at Xiyang station in Yunnan Province as a case study.Results show that the LBA algorithm is superior to PSO algorithm,and is of good convergence accuracy,robust performance and global optimization ability.Using LBA algorithm to find the best projection direction of PP model not only improves the classification accuracy of the PP model,but also provides a new way and method for the selection of the PP model. In the LBA-PP model,the annual runoff is considered,and the time history information is distributed.The classification results are more scientific and objective than those of conventional method.

Key words

annual runoff classification / bat algorithm / projection pursuit model / parameter optimization / Lévy flight strategy

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

MAO Zong-bo,DAO Hai-ya. Wet-Dry Classification of Annual Runoff Based on LBA-PP Model[J]. Journal of Changjiang River Scientific Research Institute. 2016, 33(9): 23-27 https://doi.org/10.11988/ckyyb.20150635

References

[1] 张军良,马光文,张志刚.模糊聚类法在径流丰枯特性分析中的应用[J].人民长江,2009,40 (7): 11-13.
[2] 赵太想,王文圣,周秀平.一种径流丰枯分类新方法研究[J].人民黄河,2006,28 (5): 12-13.
[3] 王文圣,向红莲,李跃清,等.基于集对分析的年径流丰枯分类新方法[J].四川大学学报(工程科学版),2008,40(5):1-6.
[4] 丁小玲,周建中,陈璐,等.基于模糊集合理论和集对原理的径流丰枯分类方法[J].水力发电学报,2015,34(5):4-9.
[5] 付强,赵小勇.投影寻踪模型原理及其应用[M].北
京:科学出版社,2006.
[6] 王柏,张忠学,李芳花,等.基于改进双链量子遗传算法的投影寻踪调亏灌溉综合评价[J].农业工程学报,2012,28(2):84-89.
[7] 陈曜,丁晶,赵永.基于投影寻踪原理的四川省洪灾评估[J].水利学报,2010,41(2):220-225.
[8] 付强,付红,王立坤.基于加速遗传算法的投影寻踪模型在水质评价中的应用研究[J].地理科学,2003,23(2):236-239.
[9] 陈广洲,汪家权,解华明.粒子群算法在投影寻踪模型优化求解中的应用[J].计算机仿真,2008,25(8):159-161,165.
[10]赵建强,戴青松,陈必科,等.基于人工蜂群-投影寻踪法的南方某河水质综合评价研究[J].节水灌溉,2014,(8):49-52.
[11]王明昊,董增川,马红亮.基于混合蛙跳与投影寻踪模型的水资源系统脆弱性评价[J].水电能源科学,2014,(9):31-35.
[12]丁红,刘东,李陶.基于改进人工鱼群算法的三江平原投影寻踪旱情评价模型[J].农业工程学报,2010,26(12):84-88.
[13]候景伟,孔云峰,孙九林.蚁群算法在需水预测模型参数优化中的应用[J].计算机应用,2012,32(10):2952-2955.
[14]YANG Xin-she. A New Metaheuristic Bat-inspired Algorithm[M]∥GONZALEZ J R,PELTA D A.Nature Inspired Cooperative Strategies for Optimization. Berlin: Springer-Verlag,2010:65-74.
[15]龙文,张文专.求解约束优化问题的改进蝙蝠算法[J].计算机应用研究,2013,31(8):2350-2353.
[16]刘长平,叶春明,刘满成.来自大自然的寻优策略:像蝙蝠一样感知[J].计算机应用研究,2013,30(5):1320-1323.
[17]刘长平,叶春明.具有Lévy飞行特征的蝙蝠算法[J].智能系统学报,2013,8(3):240-246.
[18]李煜,马良.新型全局优化蝙蝠算法[J].计算机科学,2013,40(9):225-229.