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Improvement of culture media efficiency in Internet of Things based on global numerical ant colony algorithm

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Abstract

Exploring the cultural media under the Internet of Things is not only an inevitable need to understand the cultural landscape of the Internet of Things era, but also an extension of the people themselves in the new medium. Understanding the Internet of Things as a new paradigm of media organization and production, it should clarify the technology and body in the Internet of Things, so it can clarify the objective for a relationship with the media. The Internet of Things solves the virtual interdimensional problem of information dissemination and social interaction, opening up a new vision of cultural communication. However, the Internet of Things technology makes the ideological and cultural communication channels more diverse and more complex. How to improve the efficiency of cultural media is the hotspot of current research. Therefore, this article takes cultural media as the research object and adopts the Internet of Things technology to construct the IoT culture media efficiency optimization model of the global numerical ant colony algorithm. Firstly, the population space and belief space of the cultural algorithm are redesigned by using the new bi-level evolutionary mechanism. Then, the maximum and minimum ant colony system is used to construct the population space, and the current optimal solution is improved by the 3-opt cross-transform operation in the belief space. Finally, the simulation experiments are set up to verify the effectiveness of the proposed algorithm. The experimental results show that the global numerical ant colony algorithm based on the Internet of Things is better than the traditional ant colony algorithm and the cultural ant colony algorithm, and the convergence speed is faster, which further improves the efficiency of the cultural media.

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References

  1. Razzaque MA, Milojevic-Jevric M, Palade A et al (2017) Middleware for Internet of Things: a survey. IEEE Internet Things J 3(1):70–95

    Google Scholar 

  2. Haghi M, Thurow K, Stoll R (2017) Wearable devices in Medical Internet of Things: scientific research and commercially available devices. Healthc Inform Res 23(1):4–15

    Google Scholar 

  3. Piccialli F, Chianese A (2017) The Internet of Things supporting context-aware computing: a cultural heritage case study. Mob Netw Appl 22(2):1–12

    Google Scholar 

  4. Wang YP, Dai X, Jung JJ et al (2017) Performance analysis of smart cultural heritage protection oriented wireless networks. Futur Gener Comput Syst 81(1):39–55

    Google Scholar 

  5. Al-Turjman FM, Imran M, Bakhsh ST (2017) Energy efficiency perspectives of femtocells in Internet of Things: recent advances and challenges. IEEE Access 66:99):1–99):1

    Google Scholar 

  6. Zheng Q, Gao JW (2013) Simulation of shielding attenuation optimization method in mobile network communication. Comput Simul 33(7):1749–1753

    Google Scholar 

  7. Berenzi A, Steimberg N, Boniotti J et al (2015) MRT letter: 3D culture of isolated cells: a fast and efficient method for optimizing their histochemical and immunocytochemical analyses. Microsc Res Tech 78(4):249–254

    Google Scholar 

  8. Horton P, Jaboyedoff M, Obled C (2017) Global optimization of an analog method by means of genetic algorithms. Mon Weather Rev 145(4):1275–1294

    Google Scholar 

  9. Boukouvala F, Hasan MMF, Floudas CA (2017) Global optimization of general constrained grey-box models: new method and its application to constrained PDEs for pressure swing adsorption. J Glob Optim 67(2):3–42

    MathSciNet  MATH  Google Scholar 

  10. Saini R, Anand N (2017) A multi-objective ant colony system algorithm for virtual machine placement. Int J Eng Res Appl 7(1):95–97

    Google Scholar 

  11. Gao L, Gao J, Li J et al (2017) Multiple algorithm integration based on ant colony optimization for endmember extraction from hyperspectral imagery. IEEE J Sel Top Appl Earth Obs Remote Sens 8(6):2569–2582

    Google Scholar 

  12. Umapathi N, Ramaraj N, Adlin Mano R (2012) A proactive ant colony algorithm for efficient power routing using MANET. Int J Comput Appl 58(20):33–36

    Google Scholar 

  13. Sharma V, Grover A (2016) A modified ant colony optimization algorithm (mACO) for energy efficient wireless sensor networks. Optik 127(4):2169–2172

    Google Scholar 

  14. Li Z, Tian Z, Wang Y et al (2012) A fast heuristic parallel ant colony algorithm for circles packing problem with the equilibrium constraints. J Comput Res Dev 49(9):1899–1909

    Google Scholar 

  15. Chen M, Lu S, Liu Q (2018) Global regularity for a 2D model of electro-kinetic fluid in a bounded domain. Acta Math Appl Sin Engl Ser 34(2):398–403

    MathSciNet  MATH  Google Scholar 

  16. Bo X (2017) An efficient ant colony algorithm based on wake-vortex modeling method for aircraft scheduling problem. J Comput Appl Math 317(2):157–170

    MathSciNet  MATH  Google Scholar 

  17. Gao S, Wang Y, Cheng J et al (2016) Ant colony optimization with clustering for solving the dynamic location routing problem. Appl Math Comput 285(C):149–173

    MathSciNet  MATH  Google Scholar 

  18. Choi HH, Lim SA, Kim JH (2014) An efficient expression technique for promotional video production based on IoT(the internet of things) in cultural art institutions. Multimed Tools Appl 6:1):1–1)14

    Google Scholar 

  19. Chen X, Zhang F (2019) Evaluation of news communication effect based on cognitive neuroscience. Transl Neurosci 10(1):31–36. https://doi.org/10.1515/tnsci-2019-0006

    Article  Google Scholar 

  20. Zhang LP, Chai WD, Meng SS (2017) Research on ant colony algorithm application in intelligent LED street light control. J Optoelectron·Laser 28(6):584–590

    Google Scholar 

  21. 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

    Google Scholar 

  22. Wang X, Zhao Y, Wang D et al (2013) Improved multi-objective ant colony optimization algorithm and its application in complex reasoning. Chin J Mech Eng 26(5):1031–1040

    Google Scholar 

  23. Zhang H, Bo G, Mu J et al (2017) Wheat hardness prediction research based on NIR hyperspectral analysis combined with ant colony optimization algorithm. Procedia Eng 174(1):648–656

    Google Scholar 

  24. Lu J, Zhang G, Li B et al (2018) An enriched prediction intervals construction method with hybrid intelligent optimization. Math Probl Eng 2018(2):1–10

    MathSciNet  Google Scholar 

  25. Aldwaik M, Adeli H (2014) Advances in optimization of highrise building structures. Struct Multidiscip Optim 50(6):899–919

    Google Scholar 

  26. Coley DA (2015) An introduction to genetic algorithms for scientists and engineers. Bull Volcanol Soc Jpn Second 12(1):90–91

    Google Scholar 

  27. Yan F (2019) Music recognition algorithm based on T-S cognitive neural network. Transl Neurosci 10(1):135–140. https://doi.org/10.1515/tnsci-2019-0023

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Journalism and Television Arts, Hunan University, Changsha, 410013, China

    Qixin Zhang & Zhiqiang Xiang

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  1. Qixin Zhang
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  2. Zhiqiang Xiang
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Correspondence to Zhiqiang Xiang.

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Zhang, Q., Xiang, Z. Improvement of culture media efficiency in Internet of Things based on global numerical ant colony algorithm. Pers Ubiquit Comput 24, 347–361 (2020). https://doi.org/10.1007/s00779-019-01270-9

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  • DOI: https://doi.org/10.1007/s00779-019-01270-9

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