Skip to main content
SpringerLink
Log in

Flood hazard assessment based on fuzzy clustering iterative model and chaotic particle swarm optimization

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

The target of flood hazard assessment is to establish appropriate casualty evaluation models for managing flood and alleviating loss affected by flood. Existing challenges on evaluating flood hazard level focus on how to achieve a stable and high-resolution result according to the incompatibilities between multiple attribute indicators. Base on the chaotic optimization theory, this study presents a chaotic particle swarm optimization (CPSO) algorithm to deal with a fuzzy clustering iterative model (CPSO-FCI) for evaluating flood hazards. By using a celebrated logistic chaotic map and a penalty function, the target function can be tackled more perfectly. The effectiveness of the novel hybrid method is evaluated by three representative test functions and two sets of practical flood disaster samples in China. Simulation results and comparisons show that the presented CPSO based on the logistic map is competitive and stable in performance with standard particle swarm optimization (PSO) and other advanced PSO-type approaches introduced in the literature. High resolution continuous flood rating results are obtained for fine-tune flood management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Chen S (1998) Engineering fuzzy set theory and application. State Security Industry Press, Beijing

    Google Scholar 

  • Cobos-Guzman S, Verdú E, Herrera-Viedma E, Crespo RG (2020) Fuzzy logic expert system for selecting robotic hands using kinematic parameters. J Ambient Intell Humaniz Comput 11(4):1553–1564

    Article  Google Scholar 

  • Coelho LDS, Lee CS (2008) Solving economic load dispatch problems in power systems using chaotic and gaussian particle swarm optimization approaches. Int J Electr Power 30(5):297–307

    Article  Google Scholar 

  • Diakakis M, Andreadakis E, Nikolopoulos E, Spyrou N, Gogou M, Deligiannakis G, Katsetsiadou N, Antoniadis Z, Melaki M, Georgakopoulos A et al (2019) An integrated approach of ground and aerial observations in flash flood disaster investigations. the case of the 2017 mandra flash flood in greece. Int J Disaster Risk Reduct 33:290–309

    Article  Google Scholar 

  • Estrada MAR, Koutronas E, Tahir M, Mansor N (2017) Hydrological hazard assessment: The 2014–15 malaysia floods. Int J Disaster Risk Reduct 24:264–270

    Article  Google Scholar 

  • Fonseca A, Santos M, Santos J (2018) Hydrological and flood hazard assessment using a coupled modelling approach for a mountainous catchment in portugal. Stoch Env Res Risk A 32(7):2165–2177

    Article  Google Scholar 

  • Geng J, Li MW, Dong ZH, Liao YS (2015) Port throughput forecasting by mars-rsvr with chaotic simulated annealing particle swarm optimization algorithm. Neurocomputing 147:239–250

    Article  Google Scholar 

  • Hassanvand MR, Karami H, Mousavi SF (2018) Investigation of neural network and fuzzy inference neural network and their optimization using meta-algorithms in river flood routing. Nat Hazards 94(3):1057–1080

    Article  Google Scholar 

  • He Y, Zhou J, Kou P, Lu N, Zou Q (2011) A fuzzy clustering iterative model using chaotic differential evolution algorithm for evaluating flood disaster. Expert Syst Appl 38(8):10060–10065

    Article  Google Scholar 

  • He Y, Xu Q, Yang S, Liao L (2014) Reservoir flood control operation based on chaotic particle swarm optimization algorithm. Appl Math Modell 38(17–18):4480–4492

    Article  MathSciNet  Google Scholar 

  • He Y, Wan J, Lei X, Singh H (2018) Flood disaster level evaluation using a particle swarm optimization algorithm considering decision maker’s preference. Water Sci Tech-w Sup 18(1):288–298

    Article  Google Scholar 

  • He YY, Zhou JZ, Xiang XQ, Chen H, Qin H (2009) Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling. Chaos Soliton Fract 42(5):3169–3176

    Article  Google Scholar 

  • Hu B, Yang B (2019) A particle swarm optimization algorithm for multi-row facility layout problem in semiconductor fabrication. J Ambient Intell Humaniz Comput 10(8):3201–3210

    Article  Google Scholar 

  • Huang L, Guan K, Xu T, Zhang G, Wang Q (2019) Investigation of the mechanical properties of steel using instrumented indentation test with simulated annealing particle swarm optimization. Theor Appl Fract Mech 102(1):116–121

    Article  Google Scholar 

  • Huang Z, Zhou J, Song L, Lu Y, Zhang Y (2010) Flood disaster loss comprehensive evaluation model based on optimization support vector machine. Expert Syst Appl 37(5):3810–3814

    Article  Google Scholar 

  • Ibrahim RA, Ewees AA, Oliva D, Elaziz MA, Lu S (2019) Improved salp swarm algorithm based on particle swarm optimization for feature selection. J Ambient Intell Humaniz Comput 10(8):3155–3169

    Article  Google Scholar 

  • Kennedy R, Eberhart J (1995) Particle swarm optimization. Proc IEEE Internat Conf Neural Netw IV 1000:1942–1948

    Article  Google Scholar 

  • Kuang F, Zhang S, Jin Z, Xu W (2015) A novel SVM by combining kernel principal component analysis and improved chaotic particle swarm optimization for intrusion detection. Soft Comput 19(5):1187–1199

    Article  Google Scholar 

  • Kucuk K, Bayilmis C, Sonmez AF, Kacar S (2020) Crowd sensing aware disaster framework design with iot technologies. J Ambient Intell Humaniz Comput 11(4):1709–1725

    Article  Google Scholar 

  • Li YG, Gui WH, Yang CH, Chen ZS (2008) A resilient particle swarm optimization algorithm. Control Decis 23(1):95–98

    MathSciNet  Google Scholar 

  • Liao L, Zhou J, Zou Q (2013) Weighted fuzzy kernel-clustering algorithm with adaptive differential evolution and its application on flood classification. Nat Hazards 69(1):279–293

    Article  Google Scholar 

  • Liu W, He S (2018) Dynamic simulation of a mountain disaster chain: landslides, barrier lakes, and outburst floods. Nat Hazards 90(2):757–775

    Article  Google Scholar 

  • Luechinger S, Raschky PA (2009) Valuing flood disasters using the life satisfaction approach. J Public Econ 93(3–4):620–633

    Article  Google Scholar 

  • Luo XW, Liu ZY (2015) Study on the particle swarm optimization based on double mutation. J Comput Methods Sci Eng 15(4):635–644

    MathSciNet  Google Scholar 

  • Miranda FN, Ferreira TM (2019) A simplifed approach for flood vulnerability assessment of historic sites. Nat Hazards 96(2):713–730

    Article  Google Scholar 

  • Motevalli A, Vafakhah M (2016) Flood hazard mapping using synthesis hydraulic and geomorphic properties at watershed scale. Stoch Env Res Risk A 30(7):1889–1900

    Article  Google Scholar 

  • Uysal G, Schwanenberg D, Alvarado-Montero R, Şensoy A (2018) Short term optimal operation of water supply reservoir under flood control stress using model predictive control. Water Resour Manag 32(2):583–597

    Article  Google Scholar 

  • Wang J, Ju C, Gao Y, Sangaiah AK, Kim GJ (2018) A PSO based energy efficient coverage control algorithm for wireless sensor networks. Comput Mater Contin 56(3):433–446

    Google Scholar 

  • Wang J, Gao Y, Liu W, Sangaiah A, Kim HJ (2019) An improved routing schema with special clustering using PSO algorithm for heterogeneous wireless sensor network. Sensors 19(3)

  • Yan Y, Zhang R, Wang J, Li J (2018) Modified pso algorithms with request and reset for leak source localization using multiple robots. Neurocomputing 292(1):82–90

    Article  Google Scholar 

  • Yang K, Davidson RA, Vergara H, Kolar RL, Dresback KM, Colle BA, Blanton B, Wachtendorf T, Trivedi J, Nozick LK (2019) Incorporating inland flooding into hurricane evacuation decision support modeling. Nat Hazards 96:857–878

    Article  Google Scholar 

  • Yu S (2014) Case analysis and application of Matlab optimization algorithms. Tsinghua University Press, Beijing

    Google Scholar 

  • Yu XF, Chen SY (2005) Application of fuzzy clustering iterative model to classification of flood disaster grade. Dalian Loging Daxue Xuebao/ J Dalian Univ Technol(China) 45(1):128–131

  • Zou Q, Liao L, Ding Y, Qin H (2019) Flood classification based on a fuzzy clustering iteration model with combined weight and an immune grey wolf optimizer algorithm. Water 11(1):80

    Article  Google Scholar 

Download references

Acknowledgements

This paper is funded by the National Natural Science Foundation (No.71771073), the Fundamental Research Funds for the Central Universities (PA2020GDKC0006), the CRSRI Open Research Program (Program SN CKWV2017525/KY), and the Open Research Fund of State Key Laboratory of simulation and Regulation of Water Cycle in River Basin (China Institute of Water Resources and Hydropower Research) (Grant NO IWHR-SKL-201605).

Author information

Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, China

    Yaoyao He

  2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, 230009, China

    Yaoyao He

  3. China Institute of Water Resources and Hydropower Research, Beijing, 100048, China

    Jinhong Wan

Authors
  1. Yaoyao He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jinhong Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yaoyao He.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, Y., Wan, J. Flood hazard assessment based on fuzzy clustering iterative model and chaotic particle swarm optimization. J Ambient Intell Human Comput 12, 933–942 (2021). https://doi.org/10.1007/s12652-020-02109-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-020-02109-5

Keywords

Search

Navigation