Experimental Psychology (Russia)
2019. Vol. 12, no. 2, 177–192
doi:10.17759/exppsy.2019120213
ISSN: 2072-7593 / 2311-7036 (online)
Comparative analysis of two new concepts of adaptive training
Abstract
General Information
Keywords: adaptive training, IRT, method of patterns, Markov random processes, wavelet analysis, self-learning systems.
Journal rubric: Mathematical Psychology
Article type: scientific article
DOI: https://doi.org/10.17759/exppsy.2019120213
Funding. This work has been supported by the Russian Foundation for Basic Research (Project No 17-29-07034).
For citation: Kuravsky L.S., Yuryev G.A., Dumin P.N., Pominov D.A. Comparative analysis of two new concepts of adaptive training. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2019. Vol. 12, no. 2, pp. 177–192. DOI: 10.17759/exppsy.2019120213. (In Russ., аbstr. in Engl.)
References
- Kibzun A.I., Panarin S.I. Formirovanie integral’nogo rejtinga s pomoshch’yu statisticheskoj obrabotki rezul’tatov testov // Avtomatika i telemekhanika. 2012. № 6. 119—139.
- Kibzun A.I., Vishnyakov B.V., Panarin S.I. Obolochka sistemy distancionnogo obucheniya po matematicheskim kursam // Vestnik komp’yuternyh i informacionnyh tekhnologij. 2008. № 10. S. 43—48.
- Kuravskij L.S., Marmalyuk P.A., YUr’ev G.A., Dumin P.N. CHislennye metody identifikacii markovskih processov s diskretnymi sostoyaniyami i nepreryvnym vremenem // Matematicheskoe modelirovanie. 2017. T. 29. № 5. S. 133—146.
- Kuravskij L.S., YUr’ev G.A., Ushakov D.V., YUr’eva N.E., Valueva E.A., Lapteva E.M. Diagnostika po testovym traektoriyam: metod patternov // Eksperimental’naya psihologiya. 2018. T. 11. № 2. S. 77—94. doi:10.17759/exppsy.2018110206
- Osipov G.S., Bryancev O.A. Modificirovannyj metod svodnyh pokazatelej kak metod ocenki sistem distancionnogo obucheniya dlya morskogo flota // Ekspluataciya morskogo transporta. 2007. № 3 (49). S. 48—52.
- Sologub G. B.Postroenie frejmovyh semanticheskih modelej v intellektual’noj sisteme testirovaniya // Informacionnye i telekommunikacionnye tekhnologii. 2012. № 14. S. 87—93.
- Aircraft trajectory clustering techniques using circular statistics. Yellowstone Conference Center, Big Sky, Montana, 2016. IEEE.
- Bastani V., Marcenaro L., Regazzoni C. Unsupervised trajectory pattern classification using hierarchical Dirichlet Process Mixture hidden Markov model // 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) / IEEE. 2014. P. 1—6.
- Borg I., Groenen P.J.F. Modern Multidimensional Scaling Theory and Applications // Springer. 2005. P. 140.
- Cramer H. Mathematical Methods of Statistics. Princeton: Princeton University Press. 1999. 575 p.
- Eerland W.J., Box S. Trajectory Clustering, Modelling and Selection with the focus on Airspace Protection // AIAA Infotech@ Aerospace. AIAA. 2016. P. 1—14.
- Enriquez M. Identifying temporally persistent flows in the terminal airspace via spectral clustering // Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013) / Federal Aviation Administration (FAA) and EUROCONTROL. Chicago, IL, USA: 2013. June 10—13.
- Enriquez M., Kurcz C. A Simple and Robust Flow Detection Algorithm Based on Spectral Clustering // International Conference on Research in Air Transportation (ICRAT) / Federal Aviation Administration (FAA) and EUROCONTROL. Berkeley, CA, USA, 2012. May 22—25.
- Gaffney S., Smyth P. Joint probabilistic curve clustering and alignment // Advances in Neural Information Processing Systems. Vol. 17. Cambridge, MA: MIT Press, 2005. P. 473—480.
- Gaffney S., Smyth P. Trajectory clustering with mixtures of regression models // Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. 1999. P. 63—72.
- Srivastava A., Feron E. Trajectory clustering and an application to airspace monitoring // IEEE Transactions on Intelligent Transportation Systems. 2011. Vol. 12. № 4. P. 1511—1524.
- Grevtsov N. Synthesis of control algorithms for aircraft trajectories in time optimal climb and descent // Journal of Computer and Systems Sciences International. 2008. Vol. 47. № 1. P. 129—138.
- Hung C., Peng W., Lee W. Clustering and aggregating clues of trajectories for mining trajectory patterns and routes // The VLDB Journal — The International Journal on Very Large Data Bases. 2015. Vol. 24. № 2. P. 169—192.
- Krasilshchikov M.N., Evdokimenkov V.N., Bazlev D.A. Individually adapted airborne systems for monitoring the aircraft technical condition and supporting the pilot control actions. M.: MAI Publishing House, 2011. 440 p (in Russian).
- Kuravsky L.S., Artemenkov S.L., Yuriev G.A., Grigorenko E.L. New approach to computer-based adaptive testing // Experimental Psychology. 2017. Vol. 10. № 3. P. 33—45. doi:10.17759/exppsy.2017100303
- Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Panfilova A.S. , Yuriev G.A. Mathematical aspects of the adaptive simulator concept // Psychological Science and Education. 2016. Vol. 21. № 2. P. 84—95. doi: 10.17759/pse.2016210210 (in Russian).
- Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Panfilova A.S., Yuryev G.A., Dumin P.N. A Probabilistic Model of Adaptive Training // Applied Mathematical Sciences. 2016. Vol. 10. № 48. 2369. URL: http:// dx.doi.org/10.12988/ams.2016.65168 (Accessed 13.04.2019)
- Kuravsky L.S., Marmalyuk P.A., Yurev G.A. Diagnostics of professional skills based on probability distributions of oculomotor activity// RFBR Journal. 2016. №. 3 (91). P. 72—82 (Supplement to “Information Bulletin of RFBR” № 24, in Russian).
- Kuravsky L.S., Marmalyuk P.A., Yuryev G.A. and Dumin P.N. A Numerical Technique for the Identification of Discrete-State Continuous-Time Markov Models // Applied Mathematical Sciences. , 2015. Vol. 9. № 8. P. 379—391. URL: https://doi.org/10.12988/ams. 2015.410882. (Accessed 13.02.2019)
- Kuravsky L.S., Marmalyuk P.A., Yuryev G.A., Belyaeva O.B., Prokopieva O.Yu. Mathematical foundations of flight crew diagnostics based on videooculography data // Applied Mathematical Sciences. 2016. Vol. 10. № 30. P. 1449—1466. URL: https://doi.org/10.12988/ams.2016.6122 (Accessed 3.02.2019).
- Kuravsky L.S., Marmalyuk P.A., Yuryev G.A., Dumin P.N., Panfilova A.S. Probabilistic modeling of CM operator activity on the base of the Rasch model // Proc. 12th International Conference on Condition Monitoring & Machinery Failure Prevention Technologies. Oxford, UK, June 2015.
- Kuravsky L.S., Yuriev G.A. Probabilistic method of filtering artefacts in adaptive testing // Experimental Psychology. 2012. Vol. 5. № 1. P. 119—131 (in Russian).
- Kuravsky L.S., Yuryev G.A. Certificate of state registration of the computer program № 2018660358 Intelligent System for Flight Analysis v1.0 (ISFA#1.0). — Application № 2018617617; declared 18 July 2018; registered 22 August 2018. (ROSPATENT).
- Kuravsky L.S., Yuryev G.A. Detecting abnormal activities of operators of complex technical systems and their causes basing on wavelet representations // International Journal of Civil Engineering and Technology (IJCIET). Vol. 10 (2). P. 724—742. URL: http://www.iaeme.com/IJCIET/ issues.asp?JType=IJCIET&V Type=10&IType=2. (Accessed 19.03.2019)
- Kuravsky L.S., Yuriev G.A., Dumin P.N. Estimating the Influence of Human Factor on the Activity of Operators of Complex Technical Systems in Civil Engineering with the Aid of Adaptive Diagnostics // International Journal of Civil Engineering and Technology. 2019. Vol. 10(2). P. 1930—1941, http://www. iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10 &IType=02 (Accessed 11.01.2019)
- Kuravsky L.S., Yuryev G.A. On the approaches to assessing the skills of operators of complex technical systems // Proc. 15th International Conference on Condition Monitoring & Machinery Failure Prevention Technologies. Nottingham, UK, September 2018. 25 p.
- Laxhammar R., Falkman G. Online learning and sequential anomaly detection in trajectories // IEEE Transactions on Pattern Analysis and Machine Intelligence. 2014. Vol. 36. № 6. P. 1158—1173.
- Li Z. et al. Incremental clustering for trajectories // Database Systems for Advanced Applications. Lecture Notes in Computer Science. 2010. Vol. 5982. P. 32—46.
- Markov models in the diagnostics and prediction problems: Textbook / Edited by L.S. Kuravsky. 2nd Edition, Enlarged. Moscow: MSUPE Edition, 2017. 203 p. (in Russian).
- Neal P.G. Multiresolution Analysis for Adaptive Refinement of Multiphase Flow Computations. University of Iowa, 2010. 116 p.
- Rasch G. Probabilistic models for some intelligence and attainment tests. // Copenhagen, Danish Institute for Educational Research, expanded edition (1980) with foreword and afterword by B.D. Wright. Chicago: The University of Chicago Press, 1960/1980.
- René Vidal, Yi Ma, Shankar Sastry. Generalized Principal Component Analysis / New York: Springer- Verlag, 2016. URL: http://www.springer.com/ us/book/9780387878102 (Accessed 13.04.2019)
- Rintoul M., Wilson A. Trajectory analysis via a geometric feature space approach // Statistical Analysis and Data Mining: The ASA Data Science Journal. 2015.
- Trevor F. Cox, M.A.A. Cox. Multidimensional Scaling, Second Edition. Chapman & Hall/CRC, 2001. 299 p.
- Wilson A., Rintoul M., Valicka C. Exploratory trajectory clustering with distance geometry // International Conference on Augmented Cognition / Springer. 2016. P. 263—274.
- Xiangyu Kong, Changhua Hu, Zhansheng Duan. Principal Component Analysis networks and algorithms. Springer, 2017. URL: http://www.springer.com/us/book/9789811029134 (Accessed 13.04.2019)
-
Information About the Authors
Metrics
Views
Total: 1351
Previous month: 7
Current month: 2
Downloads
Total: 479
Previous month: 1
Current month: 0