Please note that papers in English are marked «En», otherwise they are «Ru».
2013
Skipor K., Strijov V. Метод наименьших углов для логистической регрессии //
Вычислительные технологии, 2013, ? — ?.
2012
Kuznetsov M., Strijov V. Fast clustering algorithm for the objects, described by the rank-scaled distance matrix // Mathematical biology and bioinfomatics-?, 2012, ? — ?.
Motrenko A., Strijov V. Multiclass logistic regression for cardio-vascular disease forecasting // Izvestiya TulSU, Natural sciences, 2012, 1 — ?.
Sanduleanu L., Strijov V. Feature selection for autoregressive forecasting // Informational technologies, 2012, 6 — ?.
Tokmakova A., Strijov V. Estimation of hyperparameters for noise and coreccated feature selection problem // Informatics and applications, 2012, 4 — ?.
2011
Krymova E., Strijov V. Feature selection algorithms for linear regression models from finite and countable sets // Factory laboratory, 2011, 77(5) — 63-68.
Strijov V., Krymova E. Model selection in linear regression analysis // Informational technologies, 2011, 10 — 21-26.
Kuznetsov M., Strijov V. Monotonic interpolation for the rank-scaled espert estomations specification // Proceedings of Mathematical Methods of Pattern Recognition. МАКС~Пресс, 2011 — 162-165.
Kuznetsov M., Strijov V. Integral Indicators and Expert estimations of Ecological Impact // International Conference on Operations Research, 2011 — 32.
Pavlov K., Strijov V. Multilevel model selection in the bank credit scoring applications // Proceedings of Mathematical Methods of Pattern Recognition. МАКС~Пресс, 2011 — 158-161.
Strijov V., Granic G., Juric J., Jelavic B., Maricic S.A. Integral indicator of ecological impact of the Croatian thermal power plants // Energy, 2011, 36(7) — 4144-4149.
Strijov V., Krymova E., Weber G.W. Evidence optimization for consequently generated models // Mathematical and Computer Modelling, 2011, 2(17) — 10.1016/j.mcm.2011.02.017.
Strijov V. Multilevel problem selection using parameters covariance matrix analysis // Proceedings of Mathematical Methods of Pattern Recognition. МАКС~Пресс, 2011 — 154-157.
Strijov V. Specification of rank-scaled expert estimation using measured data // Factory laboratory, 2011, 77(7) — 72-78.
Strijov V. Invariants and model selection in forecasting // International Conference on Operations Research, 2011 — 133.
Skipor, K., Strijov, V. Least angle logistic regression // Intelligent Data Analysis, 2011.
Strijov, V., Granic, G., Juric, J., Jelavic, B., Maricic, S.A. // Integral Indicator of Ecological Footprint for Croatian Power Plants // Energy, 2011.
Strijov, V.V., Krymova, E.A., Weber, G.-W. Evidence Optimization for Consequently Generated Models // Mathematical and Computer Modelling, 2011.
Strijov, V.V., Krymova, E.A. Feature selection algorithms for inductively generated linear regression models // Factory laboratory, 2011.
Krymova, E.A., Strijov, V.V. Model selection in regression analysis // Informational technologies, 2011.
Skipor, K., Strijov, V. Least angle feature selection for logistic regression // Computational technologies, 2011. [Skipor10Method.pdf, Ru]
Strijov, V. Specification of rank-scaled expert estimation using measured data // Factory laboratory, 2011. [Strijov10Rankindex.pdf, Ru]
2010
Strijov V., Weber G.W. Nonlinear regression model generation using hyperparameter optimization // Computers and Mathematics with Applications 60 (2010), pp. 981-988. [ScienceDirect, En]
Strijov, V. Methods of model selection, Moscow: CCRAS, 2010, 60 p. [Strijov10Preprint.pdf, Ru]
Strijov, V., Letmathe, P. Integral indicators based on data and rank-scale expert estimations // Proceedings of conference on Intelligent data processing, 2010, pp. 107-110. [Strijov2010Integral_IOI.pdf, En]
Strijov, V.V., Krymova, E.A. Model selection and multicollinearity analysis // Proceedings of conference on Intelligent data processing, 2010, pp. 153-156. [Krymova2010Select_IOI.pdf, Ru]
Skipor, K., Strijov, V. Least angle logistic regression // Proceedings of conference on Intelligent data processing, 2010, pp. 180-183. [Skipor10LALR_IOI.pdf, Ru]
Strijov, V., Weber, G.W., Dolgopolova, I. Model Generation and Mathematical Modelling // EngOpt 2010: 2nd International Conference on Engineering Optimization, 2010, p. 169. [Strijov2010engOpt.pdf, En]
Strijov, V. Evidence of successively generated models // International Conference on Operations Research “Mastering Complexity” 2010, p. 223. [Strijov2010Evidence_OR, En]
Strijov, V. Model generation and model selection in credit scoring // 24th European Conference on Operations Research, 2010, p. 218. [Strijov10ModelGen_EURO.pdf, En]
2009
Strijov V., Sologub R. Inductive generation of the regression models for option volatility // Computational technologies. 2009. No 5. C. 102—113. [Strijov09JCT5.pdf, Ru]
Krymova E., Strijov V. Comparison of the heuristic algorithms for linear regression model selection // Mathematical methods for pattern recognition. Conference proceedings. Moscow, MAKS Press, 2009. P. 145-148. [strijov09MM1_MMRO-14.pdf, Ru]
Melnikov D., Strijov V., Anderrva E., Edenharter G. Selection of support object set for robust integral indicator construction // Mathematical methods for pattern recognition. Conference proceedings. Moscow, MAKS Press, 2009. P. 159-162. [strijov09MM2_MMRO-14.pdf, Ru]
Strijov V., Sologub R. Algorithm of nonlinear regression model selection by analysis of hyperparameters // Mathematical methods for pattern recognition. Conference proceedings. Moscow, MAKS Press, 2009. P. 184-187. [strijov09MM3_MMRO-14.pdf, Ru]
Strijov V., Granic G., Juric Z., Jelavic B., Maricic S.A. Integral Indicator of Ecological Footprint for Croatian Power Plants // HED Energy Forum “Quo Vadis Energija in Times of Climate Change” Zagreb, Croatia November 20, 2009. P. 46. [Abstact, En], [Full paper: Strijov09HED_EIHP_final.pdf, En]
Strijov V. Model Selection Using Inductively Generated Set / 23rd European Conference on Operational Research. Abstracts. Bonn, July 5-8, 2009. P. 114.
Strizhov A., Strijov V. Specification of rank-scaled expert estimations using measured data / 23rd European Conference on Operational Research. Abstracts. Bonn, July 5-8, 2009. P. 209.
Strijov V. The Inductive Algorithms of Model Generation // SIAM Conference on Computational Science and Engineering (CSE09). Abstracts. Miami, Florida, USA. March 2-6, 2009. [strijov09_SIAM_cse09.pdf, En]
Strizhov A., Strijov V. Specification of the rank-scaled expert estimations // Mathematics. Computer. Education. XVI international conference proceedings. Moscow, RCD. 2009. P. 41. [strizhov09mce.pdf, Ru]
Strijov V., Sologub R. Regression model generation of implied volatility of European options // Mathematics. Computer. Education. XVI international conference proceedings. Moscow, RCD. 2009. P. 58. [sologub09mce.pdf, Ru]
Strijov V., Krymova E. Regression model generation and selection algorithms // Mathematics. Computer. Education. XVI international conference proceedings. Moscow, RCD. 2009. P. 40. [krymova09mce.pdf, Ru]
Strijov V. Generation and selection procedures for regression models // Mathematics. Computer. Education. XVI international conference proceedings. Moscow, RCD. 2009. P. 184. [strijov09mce.pdf, Ru]
2008
Strijov V. The methods for the inductive generation of regression models. Moscow, Computing Center of RAS. 54 pages. [strijov08ln.pdf, Ru]
Strijov V., Sologub R. The inductive generation of the volatility smile models / SIAM Conference on Financial Mathematics and Engineering 2008. New Brunswick, New Jersey, USA. November 21-22, 2008. Conference abstracts. [sologub08finance_eng.pdf, En]
Strijov V. Estimation of hyperparameters on parametric regression model generation / 9th International Conference on Pattern Recognition and Image Analysis: New Information Technologies (PRIA-9-2008), Nizhni Novgorod, Russian Federation, September, 14-20, 2008. Conference Proceedings, Volume 2. Pp. 178-181. [strijov08roai_source.pdf, En]
Bray D., Strijov V. Using immune markers for classification of the CVD patients / Intellectual Data Analysis: Abstracts of the International scientific conference. Crimea scientific center NAS of Ukraine. Simferopol. 2008. P. 49—50. [bray08ioi.pdf, En], photocopy of the report [ioi08report.pdf, Ru]
Strijov, V. On the inductive model generation / Intellectual Data Analysis: Abstracts of the International scientific conference. Crimea scientific center NAS of Ukraine. Simferopol. 2008. P. 220. [strijov08ioi.pdf, En]
Gushchin A., Strijov V. An algorithm on the expert estimations objectification with measured data / Intellectual Data Analysis: Abstracts of the International scientific conference. Crimea scientific center NAS of Ukraine. Simferopol. 2008. P. 78—79. [gushchin08ioi.pdf, Ru]
Sologub R., Strijov V. The inductive construction of the volatility regression models / Intellectual Data Analysis: Abstracts of the International scientific conference. Crimea scientific center NAS of Ukraine. Simferopol. 2008. P. 215—216. [sologub08ioi.pdf, Ru]
Strijov, V. Clusterization of multidimensional time-series using dynamic time warping // Mathematics. Computer. Education. XV-th international conference. Abstracts. Moscow: R&C Dynamics. 2008. P. 28. [strijov08macoed.pdf, Ru], photocopy [strijov08mce-21.pdf, Ru]
2007
Strijov, V. The search of a parametric regression model in an inductive-generated set // Journal of Computational Technologies. 2007. No 1. P. 93-102. [strijov07JCT.pdf, Ru] or [strijov06poisk_jct_en.pdf, En]
The procedure of the search for a parametric regression model in a model set is described. The model set is a set of superpositions of given smooth functions. The model parameters density estimates are used for the search. To illustrate the approach a problem of modelling a pressure in a spray chamber of a combustion engine is included.
Strijov, V., Kazakova, T. Stable indices and the choice of a support description set // Zavodskaya Laboratoriya. 2007. No 7. P. 72-76. [stable_idx4zavlab_after_recenz.pdf, Ru] or [strijov07stable.pdf, En]
This paper describes an integral indicator construction algorithm. The integral indicator is a linear combination of the object features. The features are in the linear scale. Outliers in the features are assumed. So the problem of stable integral indicators construction arises. To construct a stable integral indicator a special-defined subset of objects is selected. A non-supervised type of algorithm is used to make the integral indicator. The proposed algorithm was applied to construct the integral indicator of the foodstuff pollution level in the Russian regions.
Strijov, V., Ptashko, O. The algorithms for the superposition search to the optimal regression models choice. Moscow: CCAS. 2007. 56 p. [occam.pdf, Ru]
The optimal regression model search procedure is described. The model is defined by a superposition of a smooth functions. Probability density functions of model parameters are used. The parameters are estimated with non-linear optimization methods. A problem of diesel engine pressure modelling presents an application of the method.
Strijov, V., Ptashko, O. The invariants construction on the set of the time series using dynamic time warping // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2007. P. 212-214. [strijov_MM_1.pdf, Ru]
Strijov, V., Kazakova, T. The rank-scaled expert estimations concordance // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2007. P. 209-211. [strijov_MM_2.pdf, Ru]
Ivakhnenko, A, Kanevskiy, D., Rudeva, A., Strijov, V. How to group marked time-series // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2007. P. 134-137. [strijov_MM_AS_4.pdf, Ru]
2006
Strijov, V. The specification on expert estimations using measured data // Zavodskaya Laboratoriya. 2006. No 7. P. 59-64. [strijov06precise.pdf, Ru]
The problem of stable integral indicators for an object set is considered. The expert estimates of the objects are used. The indicators are computed as a linear combination of the object features and corrected with the expert estimates. Well known algorithms are involved to compare the proposed method with.
Strijov, V. Indices construction using linear and ordinal expert estimations // Citizens and Governance for Sustainable Development. Abstracts. Vilnius. 2006. P. 49. [strijo06Abstract_SIGSUD_RuEng.pdf, Ru, En]
Strijov, V. The search of regression models in a superpositions of smooth functions // Mathematics. Computer. Education. XIII-th international conference. Abstracts. Moscow: Progress-Traditsia. 2006. [strijov06mce.pdf, Ru]
Strijov, V. Vsevolod Vladimirovich Shakin. // Proc. Mathematics. Computer. Education. Izhevsk: RCD. 2006. Vol. 1. P. 5-16. [VsevolodShakin06paper.pdf, Ru]
Strijov, V. The search of regression models in an inductive-generated set // Artificial intelligence. 2006. No 2. P. 234-237. [strijov06AI.pdf, Ru]
There a sample set of dependent variables and one independent variable are given. There a set of nongenerated functions, which define a set of regression models is given. The paper describes an algorithm of optimal regression model choice. The algorithm uses hyperparameters to estimate model elements importance.
Strijov, V. The search of regression models in an inductive-generate set // International scientific conference on Artificial Intelligence. Abstracts. Simferopol: Crimea Scientific Center. 2006. P. 198. [strijov2006ioi.pdf, Ru]
Kazakova, T., Strijov, V. The robust indicators with normalising functions selection // Artificial intelligence. 2006. No 2. P. 160-163. [strijov06AIidx.pdf, Ru].
The problem of stable integral indicators for an object set is considered. The objects are featured in the linear scales. To construct a stable integral indicator one has to choose an objects features subset such that causes the maximal value to the stable criterion.
Kazakova, T., Strijov, V. The robust indicators with normalising functions selection // International scientific conference on Artificial Intelligence. Abstracts. Simferopol: Crimea Scientific Center. 2006. P. 199. [strijov_kazakova2006ioi.pdf, Ru]
Strijov, V., Kazakova, T. Stable indices and the choice of a support description set // Application of the multivariate statistical analysis in economics and assessment of quality. 8-th International Conference. Abstracts. Moscow. 2006. [strijovkazakova06CEMI.pdf, Ru]
2005
Strijov, V. Mathematical modelling on the protected area management // Aktualnye problemy sovremennoi nauki. 2005. No 5. [strijov2005actualnyeproblemy.pdf, Ru]
A feedback model of control the Protected areas is described. The model involves the control subject and object. The subject set the goals of the control and according to the goals chooses one of the several variants of control. The object state monitoring is holding during the process of control. The described model involves Protected area annual reports and expert estimates.
Strijov, V. On isomorphic automata synthesis problem // Estestvennye i technicheskiye nauki. 2005. No 4. [strijov2005estestvnauki.pdf, Ru]
Ptashko, G. Strijov, V. The distance function choice for phase trajectory comparison // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2005. P. 190-191. [ptashko05mmro.pdf, Ru]
Kazakova, T., Strijov, V. The stable integral indicators construction // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2005. P. 116-119. [kazakova05mmro.pdf, Ru]
Strijov, V. The optimal complexity model choice for nonlinear regression problems // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 2005. P. 206-208. [strijov05mmro.pdf, Ru]
Strijov, V., Shakin, V. The choice of the optimal regression model // Proc. Mathematics. Computer. Education. Moscow: Progress-Traditsia. 2005. [macoed05_1.pdf, Ru]
Ptashko, G., Strijov, V., Shakin, V. Specification of the ordinal expert estimations // Proc. Mathematics. Computer. Education. Moscow: Progress-Traditsia. 2005. [macoed05_2.pdf, Ru]
2003-2004
Aivazian, S., Strijov, V. Shakin, V. On a problem of macroeconomics management // Economics and mathematical methods. Draft. Moscow: Nauka. 2003. 17 p. [macro1.pdf, Ru]
Strijov, V. Shakin, V. Forecast and control with autoregression models // Proc. Mathematical Methods of Pattern Recognition conference. Moscow: CCAS. 2003. P. 178-181. [mmro11.pdf, Ru]
Strijov, V., Shakin, V. Index construction: the expert-statistical method // Environmental research, engineering and management. 2003. No 4 (26). P.51-55. [10-v_strijov.pdf, En]. Proc. SIID-2003 International conference. Vilnus, 2003. P. 56-57. [siid03.pdf, 79 KB, En]
The paper deals with the index construction and presents a new technique that involves expert estimations of object indices as well as feature significance weights. The method based on a linear indexing model for a set of objects index is calculated as a linear combination of the object feature descriptions. Well-known methods of index construction with “no teacher” are overviewed to give a comparison with the new method. Experts can take part in the index calculation and verify the results, which are: the first, precise valid indices and the second, we have the reasoned expert estimations. The methods with or without expert involvement were used for solution of listed below different economical, sociological, and ecological problems.
2002
Strijov, V. Expert estimations concordance for integral indicators construction. Thesis manuscript. Moscow 2002. 105 p. [concordt.pdf, 945 KB, Ru] Abstract. 24 p. [concorda.pdf, Ru]
To construct an index one has to collect data on objects. After data acquisition he has a table “object-feature”. Using the table he can make the required index. For that one chooses one of mathematical methods such as Singular Components, Principle Components, Pareto Slicing and the others. The mentioned methods also called as “non-expert” methods.
Experts, that have their own opinions in particular applications, could to assign expert estimations to the objects. Expert estimations can prove or disprove the indices that were results of “non-expert” methods. The proposed technique solve problem of concordance the expert estimations and indices.
Strijov, V. Expert estimations concordance for biosystems under extreme conditions. Notes on applied mathematics. Moscow: CCAS. 2002. 41 p. [strijov280502.pdf, Ru]
The expert estimations concordance technique is considered. The specified expert-estimations were applied to the project on the State Protected Areas effectiveness evaluation. In the paper the theory of effectiveness indicators is described together with the application project results and the software library.
Strijov, V., Shakin, V. Multi-scaled object ordering. Lecture draft. Moscow. CCAS 2002. 8 p. [multiscales_indicatros.pdf, 8.1 MB, Ru]
Strijov, V., Shakin, V. Expert grade estimations concordance // International scientific conference on Artificial Intelligence. Abstracts. Simferopol: Crimea Scientific Center. 2002. P. 82-83. [ioi2002.pdf, Ru]
Strijov, V., et al. Methodology elements of the university research effectiveness estimations. Moscow: Ministry of Education. 2002. 7 p. [part1ver1.pdf, 193 KB, Ru] [part2ver2.pdf, Ru]
Strijov, V., Shakin, V. Expert grade estimations specification // Mathematics. Computer. Education. Abstracts. Moscow: Progress-Traditsia. 2002. P. 148. [macoed.pdf, Ru]
Molak, V., Strijov, V., Shakin, V. Kyoto-Index for the US power plants // Mathematics. Computer. Education. Abstracts. Moscow: Progress-Traditsia. 2002. P. 292. [kimacoed.pdf, Ru]
2001
Strijov, V., Shakin, V. Expert estimations concordance // Proc. Mathematical Methods of Pattern Recognition conference. Moscow: CCAS. 2001. P. 137-138. [mmro10.pdf, Ru]
Strijov, V., Shakin, V., Blagovidov, K. The Protected Areas Management Model. Manuscript. Moscow: WWF. 2001. 7 p. [pamodel.pdf, Ru]
Strijov, V., Shakin, V., Blagovidov, K. Expert estimations concordance for protected areas management effectiveness analysis // Multivariate statistics analysis applications in economics and quality estimation. Abstracts. Moscow: CEMI. 2001. P. 30. [cemi01ar.pdf, 612 KB, Ru] Abstract:[cemi2001.pdf, 90 KB, Ru]
Matunin, E., Izgacheva, T., Kazakova, T., Karioukhin, E., Strijov, V., Shakin, V. Mathematical modelling and informational support on gerontology organizations. Moscow: CCAS. 2001. 79 p.
Molak, V, Shakin, V. Strijov, V. Kyoto Index for the Power Plants in the USA // The 3-rd Moscow International Conference On Operations Research. Abstracts. Moscow: CCAS. 2001. P. 80.
Karioukhin, E., Shakin, V., Strijov, V., Matunin, E., Izgacheva, T., Kazakova, T. Mathematical modelling on gerontology support organizations // The Clinical Gerontology. Scientific journal. Moscow: Newdiamed. Vol. 7-8. 2001. P. 89.
Strijov, V., Shakin, V. An algorithm for clustering of the phase trajectory of a dynamic system // Mathematical Communications. Supplement 1. 2001. P. 159-165. [koi2000a.pdf, En]
This paper describes an approach to quantitative analysis of multivariate dynamic system in phase space. The system is used as mathematical model for various living systems. One of the related problems is to represent a phase trajectory as a sequence of clusters to classify the system’s state. The algorithm for partitioning a phase trajectory into clusters is presented. Input data for the algorithm is a data matrix, which corresponds to a set of sequential samples of the given phase trajectory. Optional parameters are dimension of the space and phase trajectory noise variance. The algorithm results is a tree-like graph. Phase trajectory of a dynamic system with Lorenz attractor is considered as a test problem to demonstrate the approach. The given phase trajectory was partitioned into clusters using the described algorithm.
Zubarevich, H, Tikunov, B., Krepets, V.,Strijov, V., Shakin, V. Multivariate methods for human development index estimation in Russia Federation regions // Proc. GIS for area sustainable development. Petropavlovsk-Kamchatskii. 2001. P. 84-105.
1999-2000
Strijov, V., Shakin, V. An algorithm for clustering of the phase trajectory of a dynamic system // 8-th International Conference on Operational Research. Rovinj: CRORS. 2000. P. 35. [koi2000.pdf, En]
Strijov, V., Shakin, V. Phase trajectory analysis software // Proc. Mathematical Methods of Pattern Recognition. Moscow: CCAS. 1999. P. 227-230. [mmro9.pdf, Ru]
Strijov, V., Shakin, V. Phase trajectory analysis // Problems of the complex system safety control. VII-th international conference proceedings. Moscow: RSHU. 1999. P. 156-157. [safety99.pdf, Ru]
2000-2002 (electronics)
Strijov, V. Noten on electronics development scheduling. Draft. 2002. [RnD_elektron.pdf, Ru]
Strijov, V. What is metastability and how to avoid it? Moscow: Schemotekhnica No 9. 2001.[st13-14.pdf, Ru]
Strijov, V. Live plug-in. Moscow: Schemotekhnica. No 5. 2001. P. 15-18. [s15-18.pdf, 358 KB, Ru]
Strijov, V. The IC behavior under lack of the voltage. Moscow: Schemotekhnica. No 5. 2000. P. 32-33.
Strijov, V. CMOS buffers. Moscow: Schemotekhnica. No 2. 2001. P. 20-21. [kmop.pdf, 88 KB, Ru]
Strijov, V. Bidirectional CBT chips application. Moscow: Schemotekhnica. No 2. 2001. P. 18-19. [cbt.pdf, Ru]
Strijov, V. Square pulse generators with CMOS ICs. Moscow: Schemotekhnica. No 3. 2000. P. 25-26. [gen_prym.pdf, Ru]
Strijov, V. Logic IC with 3V power supply. Moscow: Schemotekhnica. No 3. 2000. P. 14-15. [log_micro.pdf, Ru]
Strijov, V. The Simplest PCI Interface. Moscow: Schemotekhnica No 1. 2000. P. 55-57. [pci.pdf, Ru]
1996-1997 (electronics)
Strijov, V. Motorola IC for TV, Video and Multimedia. Overview. Moscow: Motorola. 1997. 75 p. [motmult.pdf, Ru]
Strijov, V. Configurable processors for biomedical data visualizing // Biosystems under extreme conditions. Ed. by Shakin, V. Moscow: CCAS. 1996. P. 47-50. [biorecon.pdf, Ru]
