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RETRACTED ARTICLE: Gauss interference ant colony algorithm-based optimization of UAV mission planning

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This article was retracted on 13 February 2024

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Abstract

To enhance the effectiveness of UAV task planning optimization scheme, a UAV task planning optimization strategy based on Gaussian disturbance ant colony optimization (ACO) was proposed. Firstly, UAV task planning optimization model with expansion observability was obtained through correlation function estimation and subsequent zero space projection, as well as closed-loop subspace identification model and block matrix filling mode; secondly, ACO was used for solving multi-objective optimization problem so as to find out optimal character subset. Then, ACO was used for optimizing UAV task planning optimization model with expansion observability. At last, the simulation experiment verified the performance advantage of the proposed algorithm in the UAV task planning optimization scheme.

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References

  1. Richtárik P, Takáč M (2016) Parallel coordinate descent methods for big data optimization. Math Program 156(1–2):433–484

    Article  MathSciNet  Google Scholar 

  2. Lai M, Tong X (2017) A metaheuristic method for vehicle routing problem based on improved ant colony optimization and Tabu search. J Ind Manag Optim 8(2):469–484

    Article  MathSciNet  Google Scholar 

  3. Leutenegger Stefan, Lynen Simon, Bosse Michael (2015) Keyframe-based visual-inertial odometry using nonlinear optimization. Int J Robot Res 34(3):314–334

    Article  Google Scholar 

  4. Tabakhi S, Moradi P, Akhlaghian F (2014) An unsupervised feature selection algorithm based on ant colony optimization. Eng Appl Artif Intell 32(6):112–123

    Article  Google Scholar 

  5. Xu Y, Li K, Hu J et al (2014) A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues. Inf Sci 270(6):255–287

    Article  MathSciNet  Google Scholar 

  6. Tawfeek MA, El-Sisi A, Keshk AE et al (2014) Cloud task scheduling based on ant colony optimization. In: International Conference on Computer Engineering & Systems. IEEE, pp 64–69

  7. Liao T, Socha K, Oca MAMD et al (2014) Ant colony optimization for mixed-variable optimization problems. IEEE Trans Evol Comput 18(4):503–518

    Article  Google Scholar 

  8. Raza MQ, Khosravi A (2015) A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings. Renew Sustain Energy Rev 50:1352–1372

    Article  Google Scholar 

  9. Yan J, Cho M, Zha H et al (2016) Multi-graph matching via affinity optimization with graduated consistency regularization. IEEE Trans Pattern Anal Mach Intell 38(6):1228–1242

    Article  PubMed  Google Scholar 

  10. Yahyanejad S, Rinner B (2015) A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs. Isprs J Photogramm Remote Sens 104:189–202

    Article  ADS  Google Scholar 

  11. Basri MAM, Husain AR, Danapalasingam KA (2015) Enhanced Backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle. J Intell Robot Syst 79(2):295–321

    Article  Google Scholar 

  12. Hao C, Orlando D, Foglia G et al (2015) Adaptive radar detection and range estimation with oversampled data for partially homogeneous environment. IEEE Signal Process Lett 22(9):1359–1363

    Article  ADS  Google Scholar 

  13. Li T, Corchado JM, Bajo J et al (2016) Effectiveness of Bayesian filters: an information fusion perspective. Inf Sci 329:670–689

    Article  Google Scholar 

  14. Sarvaghad-Moghaddam Moein, Orouji Ali A, Ramezani Zeinab, Elhoseny Mohamed, Farouk Ahmed, Arun Kumar N (2018) Modelling the spice parameters of SOI MOSFET using a combinational algorithm. Cluster Comput. https://doi.org/10.1007/s10586-018-2289-6

    Article  Google Scholar 

  15. Elhoseny M, Ramírez-González G, Abu-Elnasr OM, Shawkat SA, Arunkumar N, Farouk A (2018) Secure medical data transmission model for IoT-based healthcare systems. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2817615

    Article  Google Scholar 

  16. Vardhana M, Arunkumar N, Abdulhay E, Ramirez-Gonzalez G (2018) Convolutional neural network for bio-medical image segmentation with hardware acceleration. Cognit Syst Res 50:10–14

    Article  Google Scholar 

  17. Tharwat A, Elhoseny M, Hassanien AE, Gabel T, Arunkumar N (2018) Intelligent Bézier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm. Cluster Comput. https://doi.org/10.1007/s10586-018-2360-3

    Article  Google Scholar 

  18. Abdulhay E, Elamaran V, Arunkumar N, Venkatraman V (2018) Fault-tolerant medical imaging system with quintuple modular redundancy (QMR) configurations. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-018-0748-9

    Article  Google Scholar 

  19. Abdulhay E, Arunkumar N, Narasimhan K, Vellaiappan E, Venkatraman V (2018) Gait and tremor investigation using machine learning techniques for the diagnosis of Parkinson disease. Future Gener Comput Syst 83:366–373. https://doi.org/10.1016/j.future.2018.02.009

    Article  Google Scholar 

  20. Vardhana M, Arunkumar N, Abdulhay E (2018) Iot based real time trafic control using cloud computing. Cluster Comput. https://doi.org/10.1007/s10586-018-2152-9

    Article  Google Scholar 

  21. Abdulhay E, Mohammed MA, Ibrahim DA, Arunkumar N, Venkatraman V (2018) Computer aided solution for automatic segmenting and measurements of blood leucocytes using static microscope images. J Med Syst. https://doi.org/10.1007/s10916-018-0912-y

    Article  PubMed  Google Scholar 

  22. Arunkumar N, Ramkumar K, Venkatraman V (2018) Entropy features for focal EEG and non focal EEG. J Comput Sci. https://doi.org/10.1016/j.jocs.2018.02.002

    Article  Google Scholar 

  23. Liu C, Arunkumar N (2018) Risk prediction and evaluation of transnational transmission of financial crisis based on complex network. Cluster Comput. https://doi.org/10.1007/s10586-018-1870-3

    Article  Google Scholar 

  24. Meng G, Arunkumar N (2018) Construction of employee training program evaluation system of three exponential forecast based on sliding window. Cluster Comput. https://doi.org/10.1007/s10586-017-1652-3

    Article  Google Scholar 

  25. Chen X, Pang L, Guo P, Sun X, Xue Z, Arunkumar N (2017) New upper degree of freedom in transmission system based on wireless G-MIMO communication channel. Cluster Comput. https://doi.org/10.1007/s10586-017-1513-0

    Article  Google Scholar 

  26. Hamza Rafik, Muhammad Khan, Arunkumar N, González GR (2017) Hash based encryption for keyframes of diagnostic hysteroscopy. IEEE Access. https://doi.org/10.1109/ACCESS.2017.2762405

    Article  Google Scholar 

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Acknowledgements

Tianjin City High School Science & Technology Fund Planning Project, China (No. 20140808).

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Authors and Affiliations

  1. Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin, 300387, China

    Fanlei Yan

  2. School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin, 300387, China

    Fanlei Yan

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  1. Fanlei Yan
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Correspondence to Fanlei Yan.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11227-024-05982-5

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Yan, F. RETRACTED ARTICLE: Gauss interference ant colony algorithm-based optimization of UAV mission planning. J Supercomput 76, 1170–1179 (2020). https://doi.org/10.1007/s11227-018-2540-1

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