Article in Russian
For citation: Alexandrov A.E., Tyurin A.V. Software tools for computing experiment aimed at multivariate analysis implementation.
Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol. 15, no. 5, pp. 907–915.
Abstract
A concept for organization and planning of computational experiment aimed at implementation of multivariate analysis of complex multifactor models is proposed. It is based on the generation of calculations tree. The logical and structural schemes of the tree are given and software tools, as well, for the automation of work with it: calculation generation, carrying out calculations and analysis of the obtained results. Computer modeling systems and such special-purpose systems as RACS and PRADIS do not solve the problems connected with effective carrying out of computational experiment, consisting of its organization, planning, execution and analysis of the results. Calculation data storage for computational experiment organization is proposed in the form of input and output data tree. Each tree node has a reference to the calculation of model step performed earlier. The storage of calculations tree is realized in a specially organized directory structure. A software tool is proposed for creating and modifying design scheme that stores the structure of one branch of the calculation tree with the view of effective planning of multivariate calculations. A set of special-purpose software tools gives the possibility for the quick generation and modification of the tree, addition of calculations with step-by-step change in the model factors. To perform calculations, software environment in the form of a graphical user interface for creating and modifying calculation script has been developed. This environment makes it possible to traverse calculation tree in a certain order and to perform serial and parallel initiation of computational modules. To analyze the results, software tool has been developed, operating on the base of the tag tree. It is a special tree that stores input and output data of the calculations in the set of changes form of appropriate model factors. The tool enables to select the factors and responses of the model at various steps and to form easyto-read tables and graphs of functions for the selected parameters. The proposed solution has been tested in the process of verification for “Prognoz_R” software, greatly simplifying the preparation and carrying out of the design calculations for analysis of the developed computational model. Thus, the proposed software tools, due to the lack of universal ready-made solutions, can serve as an effective replacement for manual carrying out of computational experiments.
Keywords: multivariate analysis, calculations tree, tag tree, analysis of calculation results, computational experiment.
References
1. Kahaner D., Moler C., Nash S. Numerical Methods and Software. Prentice Hall, 1988, 504 p.
2. Frolov K.V., Vorob'ev Yu.L., Laverov N.P. Bezopasnost' Rossii. Analiz riska i Problem Bezopasnosti. Chast'
3. Prikladnye Voprosy Analiza Riskov Kriticheski Vazhnykh Ob"ektov. Moscow, MGF Znanie Publ., 2007, 815 p.
3. Aleksandrov A.E., Mikhailov B.M., Tyurin A.V. Ensuring safe operation of nuclear power facilities based on the standards for the certification and verification software. Sbornik Trudov IV Mezhdunarodnoi Konferentsii "IT-Standart 2014" [Proc. IV Int. Conf. IT-Standart 2014]. Moscow, 2014, pp. 56–64.
4. Lavrov V.V., Spirin N.A. Metody Planirovaniya i Obrabotki Rezul'tatov Inzhenernogo Eksperimenta [Planning Techniques and Data Processing Methods in Engineering Experiment]. Ekaterinburg, UGTU-UPI Publ., 2004, 257 p.
5. Aleksandrov A.E., Vostrikov A.A., Tyurin A.V. Otchet o verifikatsii programmnogo sredstva «Prognoz_R» dlya PEVM po raschetu veroyatnosti khrupkogo razrusheniya korpusa reaktora RU VVER-1000 [Report on the verification software "Prognoz_R" for PC on the calculation of the probability of brittle fracture of the reactor pressure vessel VVER-1000]. Reg. no. 01201460046.
6. Arlazarov V.L., Emel'yanov N.E. Upravlenie Informatsionnymi Potokami [Management of Information Flows]. Moscow, Editorial URSS Publ., 2002, 368 p.
7. Gathen J., Gerhard J. Modern Computer Algebra. 3rd ed. Cambridge University Press, 2013, 808 p.
8. Klemens B. Modeling with Data: Tools and Techniques for Scientific Computing. Princeton University Press, 2008, 468 p.
9. Muller K.E., LaVange L.M., Ramey S.L. Power calculations for general linear multivariate models including repeated measures applications. Journal of the American Statistical Association, 1992, pp. 1209–1226.
10. Gurman V.I., Matveev G.A., Trushkova E.A. Socio-ecological-economic region model in parallel computing. Upravlenie Bolsimi Sistemami, 2011, no. 32, pp. 109–130.
11. Kandiev Ya.Z., Malakhov A.A., Serova E.V., Spirina S.G. Estimation of the effect of small perturbations in multivariant calculations using the prizma-D computer program. Atomic Energy, 2005, vol. 99, no. 3, pp. 639–645. doi: 10.1007/s10512-005-0259-6
12. Kovalev G.F., Lebedeva L.M. Kompleks Modelei Optimizatsii Rezhimov Raschetnykh Sostoyanii pri Otsenke Nadezhnosti Elektroenergeticheskikh System [Complex Models Optimization of Settlement States for Reliability Estimation of Electric Power Systems]. Irkutsk, Institut Sistem Energetiki SO RAN, 2000, 73 p.
13. Roberts K.V. An introduction to the OLYMPUS system. Computer Physics Communication, 1974, vol. 7, no. 5, pp. 237–243. doi: 10.1016/0010-4655(74)90025-3
14. Gorbunov-Posadov M.M., Karpov V.Ya., Koryagin D.A., Krasotchenko V.V., Matekin M. P. Safra: software for computing experiment. In Pakety Prikladnykh Programm. Vychislitel'nyi Eksperiment [Application Software. Computational Experiment]. Moscow, Nauka Publ., 1983, pp. 12–50. (In Russian)
15. Ivanov A.V. Results and algorithms control system for digital modeling tasks. Avtomatizatsiya i Sovremennye Tekhnologii, 2007, no. 12, pp. 29–34.
16. Mnogovariantnyi Analiz. Programmnyi Kompleks dlya Avtomatizatsii Modelirovaniya Nestatsionarnykh Protsessov v Mekhanicheskikh Sistemakh. Available at: http://www.laduga.ru/pradis/help/pradis/PRADIS_Multivaria_analysis.ru.htm (accessed: 25.12.2014).
17. Hinkelmann K., Kempthorne O. Design and Analysis of Experiments, Volume I: Introduction to Experimental Design. 2nd ed. Wiley, 2008, 667 p.
18. Hinkelmann K., Kempthorne O. Design and Analysis of Experiments, Volume II: Advanced Experimental Design. 1st ed. Wiley, 2005, 780 p.
19. Goos P., Jones B. Optimal Design of Experiments: A Case Study Approach. Wiley, 2011, 304 p.
20. Aleksandrov A.E., Vostrikov A.A., Tyurin A.V. Probabilistic calculations based on Monte Carlo simulation using multivariate analysis. VI Mezhvuzovskii Sbornik Nauchnykh Trudov [VI Interuniversity Collection of Proceedings]. Moscow, MGUP Publ., 2012, pp. 189–194. (In Russian)
21. Post F.H., Nielson G.M., Bonneau G.-P. Data Visualization: The State of the Art. Springer, 2003, 443 p. doi: 10.1007/978-1-4615-1177-9
22. Afanas'eva N.Yu. Computational and Experimental Methods of Research. Moscow, KRONUS Publ., 2010, 336 p.
23. Attestation Passport of software Prognoz_R 1.0. Registered 17.04.2014, no. 358.
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