Skip to main content
SpringerLink
Log in

An Investigation of Research Activities in Intelligent Data Processing Using Data Envelopment Analysis

  • Chapter
  • First Online:
Computer Vision in Control Systems—6

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 182))

Abstract

The report implements a vision of intelligent data processing task and elaboration of the efficiency evaluation using data envelopment analysis in discussions on the problem investigations of advanced technology precursors. Data processing aspect of a collaboration of advanced processes from the standpoint of pervasive informatics is presented. The target setting corresponds to an initiative focused on a comprehensive discussion of geosocial networking formation issues, assessment of the quality of intelligent data processing based on conceptual models of integration advanced technology of computer vision and location-based social networks, and innovative potential of distributed computer vision and collaborative innovation network. The representations of hybrid optimization modeling and control of intelligent transport systems are of interest in the modern conditions of rapid development of artificial neural networks, cognitive and other intelligent data processing technologies. In this regard, a interdisciplinary research is directly aimed at the implementation of effective common-based peer production of the geosocial networking in the transition to intelligent production technologies and new materials by creating the original tools of data envelopment analysis (free disposal hull) for the search, collection, storage, and processing of pertinent information resources, in particular together object-based image analysis. A convergence of professional, scientific, and educational network communities and prerequisites for its implementation at research activities are discussed. Primarily, a short description of data envelopment analysis is presented and followed by the overview of integration components, which use the distributed computer and telecommunication networks. Hereinafter, we investigate the opportunities of intelligent data processing in object-based image analysis for location-based social networks. Presented hybrid optimization modeling framework is used at experimental studies.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Liu, K.: Pervasive informatics in intelligent spaces for living and working. In: 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, vol. 2, pp. XVIII–XIX (2008)

    Google Scholar 

  2. Co-operative Intelligent Transport Systems (ITS)—Local Dynamic Map, Intelligent Transport Systems, ISO 18750:2018. Available at: https://www.iso.org/standard/69433.html. Accessed 26 Aug 2019

  3. Dedicated Short Range Communication (DSRC)—DSRC Application Layer, Intelligent Transport Systems, ISO 15628:2013. Available at: https://www.iso.org/standard/59288.html. Accessed 26 Aug 2019

  4. Ryvkin, S., Rozhnov, A., Lobanov, I.: Convergence of technologies of the evolving prototype of an energy efficient large-scale system. In: 2018 20th International Symposium on Electrical Apparatus and Technologies, pp. 1–4 (2018)

    Google Scholar 

  5. Pham, M.C., Klamma, R., Jarke, M.: Development of computer science disciplines: a social network analysis approach. Soc. Netw. Anal. Min. 1(4), 321–340 (2011)

    Article  Google Scholar 

  6. Rozhnov, A.V., Melikhov, A.A.: Vectorizing textual data sources to decrease attribute space dimension. In: 2017 10th International Conference Management of Large-Scale System Development, pp. 1–4 (2017)

    Google Scholar 

  7. McFaddin, S., Coffman, D., Han, J.H., Jang, H.K., Kim, J.H., Lee, J.K., Moon, Y.S., Narayanaswami, C., Paik, Y.S., Park, J.W., Soroker, D.: Celadon: delivering business services to mobile users in public spaces. IBM Research Report, RC24381 (2007)

    Google Scholar 

  8. Moran, S., Nakata, K.: Ubiquitous monitoring and behavioural change: a semiotic perspective. In: 11th International Conference on Informatics and Semiotics in Organisations, Beijing, China, pp. 449–456 (2009)

    Google Scholar 

  9. Liu, K., Nakata, K., Harty, C.: Pervasive informatics: theory, practice and future directions. Intell. Build. Int. 2(1), 5–19 (2010)

    Article  Google Scholar 

  10. Favorskaya, M., Buryachenko, V.: Fast salient object detection in non-stationary video sequences based on spatial saliency maps. In: De Pietro, G., Gallo, L., Howlett, R.J., Jain, L.C. (eds.) Intelligent Interactive Multimedia Systems and Services. SIST, vol. 55, pp. 121–132. Springer International Publishing, Switzerland (2016)

    Google Scholar 

  11. Rozhnov, A.V., Lobanov, I.A.: Investigation of the joint semantic environment for heterogeneous robotics. In: 2017 10th International Conference Management of Large-Scale System Development, pp. 1–5 (2017)

    Google Scholar 

  12. The International Charter Space and Major Disasters. Available at: https://disasterscharter.org/web/guest/home. Accessed 26 Aug 2019

  13. Location-Based Social Networks. Available at: https://www.microsoft.com/en-us/research/project/location-based-social-networks/. Accessed 26 Aug 2019

  14. Blaschke, T., Lang, S., Hay, G.J. (eds.): Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Springer Science & Business Media (2008)

    Google Scholar 

  15. Rozhnov, A., Zhuravleva, N., et al.: Technology and software complex environment analysis of complex systems. In: Seoul International Invention Fair (SIIF 2012), Seoul, Korea (2012)

    Google Scholar 

  16. Nechaev, V., Goncharenko, V., Rozhnov, A., Lytchev, A., Lobanov, I.: Integration of virtual semantic environments components and generalized data envelopment analysis (DEA) model. In: CEUR Workshop Proceedings: Selected Papers of the XI International Scientific-Practical Conference Modern Information Technologies and IT-Education, vol. 1761, pp. 339–347 (2016)

    Google Scholar 

  17. Cooper, W.W., Seiford, L.M., Tone, K.: Data Envelopment Analysis. A Comprehensive Text with Models, Applications, References and DEA-Solver Software, 2nd edn. Springer Science and Business Media, New York (2007)

    Google Scholar 

  18. Krivonozhko, V., Rozhnov, A., Lychev, A.: Construction a hybrid intelligent information framework and components of expert systems using the generalized DEA model. Neurocomputers (6), 3–12 (in Russian) (2013)

    Google Scholar 

  19. Emrouznejad, A., Yang, G.: A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Econ. Plan. Sci. 61, 4–8 (2018)

    Article  Google Scholar 

  20. Briec, W., Kerstens, K., Eeckaut, P.V.: Non-convex technologies and cost functions: definitions, duality and nonparametric tests of convexity. J. Econ. 81(2), 155–192 (2004)

    Article  Google Scholar 

  21. Krivonozhko, V.E., Førsund, F.R., Lychev, A.V.: Measurement of returns to scale using a non-radial DEA model. Eur. J. Oper. Res. 232(3), 664–670 (2014)

    Article  MathSciNet  Google Scholar 

  22. Krivonozhko, V.E., Lychev, A.V.: Algorithms for construction of efficient frontier for nonconvex models on the basis of optimization methods. Dokl. Math. 96(2), 541–544 (2017)

    Article  MathSciNet  Google Scholar 

  23. Krivonozhko, V.E., Lychev, A.V.: Frontier visualization for nonconvex models with the use of purposeful enumeration methods. Dokl. Math. 96(3), 650–653 (2017)

    Article  Google Scholar 

  24. Podinovski, V.V.: Returns to scale in convex production technologies. Eur. J. Oper. Res. 258(3), 970–982 (2017)

    Article  MathSciNet  Google Scholar 

  25. Deprins, D., Simar, L., Tulkens, H.: Measuring labor efficiency in post offices. In: Marchand, M., Pestieau, P., Tulken, H. (eds.) The Performance of Public Enterprises: Concepts and Measurements, pp. 243–268. Springer, Boston, MA (1984)

    Google Scholar 

  26. Volodin, A.V., Krivonozhko, V.E., Ryzhikh, D.A., Utkin, O.B.: Construction of three-dimensional sections in DEA by using parametric optimization algorithms. Comput. Math. Math. Phys. 44(4), 589–603 (2004)

    MathSciNet  MATH  Google Scholar 

  27. Giokas, D.I., Pentzaropoulos, G.C.: Evaluating the relative operational efficiency of large-scale computer networks: an approach via data envelopment analysis. Appl. Math. Model. 19(6), 363–370 (1995)

    Article  Google Scholar 

  28. Kamiyama, N.: Network topology design using data envelopment analysis. In: IEEE Global Telecommunications Conference, pp. 508–513 (2007)

    Google Scholar 

  29. Zhou, Y., Ai, B.: Evaluation of high-speed train communication handover models based on DEA. In: 2014 IEEE 79th Vehicular Technology Conference, pp. 1–5 (2014)

    Google Scholar 

  30. Wang, Z., Zhang, L., Liu, X., Fan, Y.F.: Evaluation of distribution communication network various access means basing on preferable DEA. In: 2009 Asia-Pacific Power and Energy Engineering Conference, pp. 1–4 (2009)

    Google Scholar 

  31. Soja, J.S., Luka, M.K., Thuku, I.T., Girei, S.H.: Comparison of performance efficiency of improved network coding multicast algorithms using data envelopment analysis. Commun. Appl. Electron. 5(2), 6–10 (2016)

    Article  Google Scholar 

  32. Ajibesin, A.A., Ventura, N., Chan, H.A., Murgu, A.: Service productivity in IT: a network efficiency measure with application to communication systems. In: Emrouznejad, A., Cabanda, E. (eds.) Managing Service Productivity: Using Frontier Efficiency Methodologies and Multicriteria Decision Making for Improving Service Performance, pp. 241–261. Springer Berlin Heidelberg, Berlin, Heidelberg (2014)

    Google Scholar 

  33. Papanikolaou, A., Wang, H., Miranda, M., Catthoor, F.: Power-aware configurable driver circuits for lines terminated by a load. Patent USA US20050280443A1, Priority date: 2004-06-18

    Google Scholar 

  34. Evaluation method and device for network planning. CN106454857A, Priority date: 2015-08-13

    Google Scholar 

  35. Cooperative game and DEA (Data Envelopment Analysis) based method for sharing fixed cost of power transmission system. CN105160490A, Priority date: 2015-09-30

    Google Scholar 

  36. Investment planning method and system based on power grid resources. CN106991516A, Priority date: 2017-01-13

    Google Scholar 

  37. Krivonozhko, V.E., Førsund, F.R., Lychev, A.V.: Measurement of returns to scale in radial DEA models. Comput. Math. Math. Phys. 57(1), 83–93 (2017)

    Article  MathSciNet  Google Scholar 

  38. Abrosimov, V., Ryvkin, S., Goncharenko, V., Rozhnov, A., Lobanov, I.: Identikit of modifiable vehicles at virtual semantic environment. In: International Conference on Optimization of Electrical and Electronic Equipment and International Aegean Conference on Electrical Machines and Power Electronics (ACEMP), pp. 905–910 (2017)

    Google Scholar 

  39. Rozhnov, A., Lychev, A.: System integration of research activities and innovations in distributed computer and telecommunication networks using data envelopment analysis. In: 21st International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications, vol. 1, pp. 273–280 (2018)

    Google Scholar 

  40. Ryvkin, S., Rozhnov, A., Lobanov, I., Chernyshov, L.: Investigation of the stratified model of virtual semantic environment for modifiable vehicles. In: 20th International Symposium on Electrical Apparatus and Technologies, pp. 1–4 (2018)

    Google Scholar 

  41. Ryvkin, S., Rozhnov, A., Lychev, A., Lobanov, I., Fateeva, Y.: Multiaspect modeling of infrastructure solutions at energy landscape as virtual semantic environment. In: International Conference on Optimization of Electrical and Electronic Equipment and International Aegean Conference on Electrical Machines and Power Electronics, pp. 935–940 (2017)

    Google Scholar 

  42. Caulfield, B., Bailey, D., Mullarkey, S.: Using data envelopment analysis as a public transport project appraisal tool. Transp. Policy 29, 74–85 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by the Russian Science Foundation, project No. 17-11-01353 (implementation of DEA approach). Partially financial support from the RFBR according to the research projects No. 17-06-00237 (investigation of innovative potential), and No. 18-311-00267 (investigation of research activities and knowledge extraction for the optimization modeling system) is also gratefully acknowledged. This research was partially supported by the Presidium of the Russian Academy of Sciences, Program No. 30 “Theory and Technologies of Multi-level Decentralized Group Control under Confrontation and Cooperation” (investigation of smart infrastructure from ITS).

Author information

Authors and Affiliations

  1. National University of Science and Technology “MISiS” (NUST MISiS), 4, Leninskiy Ave., Moscow, 119049, Russian Federation

    Andrey V. Lychev & Aleksei V. Rozhnov

  2. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences (ICS RAS), 65, Profsoyuznaya Street, Moscow, 117997, Russian Federation

    Aleksei V. Rozhnov & Igor A. Lobanov

Authors
  1. Andrey V. Lychev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aleksei V. Rozhnov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Igor A. Lobanov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andrey V. Lychev .

Editor information

Editors and Affiliations

  1. Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Faculty of Engineering and Information Technology, Technology Centre for Artificial Intelligence, University of Technology Sydney, Broadway, NSW, Australia

    Lakhmi C Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Lychev, A.V., Rozhnov, A.V., Lobanov, I.A. (2020). An Investigation of Research Activities in Intelligent Data Processing Using Data Envelopment Analysis. In: Favorskaya, M., Jain, L. (eds) Computer Vision in Control Systems—6. Intelligent Systems Reference Library, vol 182. Springer, Cham. https://doi.org/10.1007/978-3-030-39177-5_10

Download citation

Publish with us

Policies and ethics

Search

Navigation