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The UAV Landing Quality Evaluation Research Based on Combined Weight and VIKOR Algorithm

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Abstract

This paper aims to use the VIKOR method to evaluate the landing quality of unmanned aerial vehicle (UAV) based on flight parameters, determining the parameter interval of the landing quality classification. At present, the evaluation of UAV landing quality mainly depends on experts’ experience or single parameter exceeding the limit, whose results are inevitably lack of scientific and objectivity. In order to improve this problem, we evaluated the landing quality with multiple flight parameters, and determined the absolute criteria using the resulting ranking. Firstly, analyzed the influence of flight parameters on the landing quality, and determined the decision matrix. Secondly, use the combination weighting method consisting of the precedence chart method and the entropy weight method to determine the weights. Moreover, VIKOR was selected as the method, whose results was given by comprehensive evaluation with sorts of flight parameters. And then we took the original data that landing sorties was in the top 20% VIKOR ranking and determined the absolute criteria for UAV landing quality evaluation. Finally, compared the evaluation results of the TOPSIS and VIKOR, it can be known that there is a high similarity between TOPSIS and VIKOR ranking with correlation coefficient 0.917, but the VIKOR method is better in UAV landing quality evaluation.

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References

  1. Kun, Z., Lixin, W., & Xiangsheng, T. (2011). Flying qualities reduction of fly-by-wire commercial aircraft with reconfiguration flight control laws. Procedia Engineering, 17, 179–196.

    Article  Google Scholar 

  2. Wang, L., Wu, C., & Sun, R. (2014). An analysis of flight quick access recorder (QAR) data and its applications in preventing landing incidents. Reliability Engineering and System Safety, 127, 86–96.

    Article  Google Scholar 

  3. Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials and Design, 121, 237–253.

    Article  Google Scholar 

  4. Villacreses, G., Gaona, G., Martínez-Gómez, J., & Jijón, D. J. (2017). Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable Energy, 109, 275–286.

    Article  Google Scholar 

  5. Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.

    Article  MATH  Google Scholar 

  6. Hajiagha, S. H. R., Mahdiraji, H. A., Zavadskas, E. K., & Hashemi, S. S. (2014). Fuzzy multi-objective linear programming based on compromise VIKOR method. International Journal of Information Technology and Decision Making, 13(04), 679–698.

    Article  Google Scholar 

  7. Zhu, G. N., Hu, J., Qi, J., Gu, C. C., & Peng, Y. H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29(3), 408–418.

    Article  Google Scholar 

  8. Tiwari, V., Jain, P. K., & Tandon, P. (2016). Product design concept evaluation using rough sets and VIKOR method. Advanced Engineering Informatics, 30(1), 16–25.

    Article  Google Scholar 

  9. Hafezalkotob, A., & Hafezalkotob, A. (2017). Interval target-based VIKOR method supported on interval distance and preference degree for machine selection. Engineering Applications of Artificial Intelligence, 57, 184–196.

    Article  MATH  Google Scholar 

  10. Malela-Majika, J. C., Chakraborti, S., & Graham, M. A. (2016). Distribution-free precedence control charts with improved runs-rules. Applied Stochastic Models in Business and Industry, 32(4), 423–439.

    Article  MathSciNet  Google Scholar 

  11. Liu, F., Zhao, S., Weng, M., & Liu, Y. (2017). Fire risk assessment for large-scale commercial buildings based on structure entropy weight method. Safety Science, 94, 26–40.

    Article  Google Scholar 

  12. Rao, R. V., & Patel, B. K. (2010). A subjective and objective integrated multiple attribute decision making method for material selection. Materials and Design, 31(10), 4738–4747.

    Article  Google Scholar 

  13. Zhao, J., Jin, J., Zhu, J., Xu, J., Hang, Q., Chen, Y., et al. (2016). Water resources risk assessment model based on the subjective and objective combination weighting methods. Water Resources Management, 30(9), 1–16.

    Article  Google Scholar 

  14. Kuo, T. C., Hsu, C. W., & Li, J. Y. (2015). Developing a green supplier selection model by using the DANP with VIKOR. Sustainability, 7(2), 1661–1689.

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the National Natural Science Foundation of China (Grants: 71501007 and 71672006). The study is also sponsored by the Technical Research Foundation and the Graduate Student Education and Development Foundation of Beihang University.

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Correspondence to Xiaoduo Qiao.

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Zhou, S., Qian, S., Qiao, X. et al. The UAV Landing Quality Evaluation Research Based on Combined Weight and VIKOR Algorithm. Wireless Pers Commun 102, 2047–2062 (2018). https://doi.org/10.1007/s11277-018-5254-z

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  • DOI: https://doi.org/10.1007/s11277-018-5254-z

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