Mathematical models of socio-economic processes
System analysis in medicine and biology
Cognitive technology
A.A. Kukushkin Information model and measure of validity of the wireframe solution as an implementation of the minimum heuristic principle
Methods of artificial intelligence and intelligent systems
A.A. Kukushkin Information model and measure of validity of the wireframe solution as an implementation of the minimum heuristic principle

Abstract.

The problem of estimated the validity of decisions on the example of a reduced model of the organizational action plan is considered. As a mathematical measure, we introduce the function of normalized residual uncertainty, which implements the minimum heuristic principle. The concept of t-norm and frame-oriented approach to the description of the subject area is used. The function is designed to assess decision support systems, planning methods and the formation of modern standards of managerial work.

Keywords:

normalized residual uncertainty of the solution, frame-oriented solution, measure of validity of the wireframe solution, information planning model.

PP. 83-95.

DOI: 10.14357/20790279190108

References

1. D. Dubois and H. Prade. 1988. Théorie des possibilities: applications à la représentation des connaissances en informatique. 2e éd. rev. et augm. Masson, Paris, 292 p.
2. Zadeh Lotfi A. Outline of a new approach to the analysis of complex systems and decision process. IEEE Transactions on Systems, Man, and Cybernetics (Volume: SMC-3, Issue:1, Jan. 1973) P 28-44.
3. Larichev O.I. 2006. Verbalny analys reshenij / pod red. A. B. Petrovsky. [Verbal decision analysis / ed. by A. B. Petrovsky]. Moscow: Nauka. 181 p.
4. Mazurov V.D. 1990. Metod komitetov v zadathach optimizacii I klassifikacii. [Method of committees in optimization and classification problems]. Moscow: Nauka. 248 p.
5. John Von Neumann, Oskar Morgenstern. 1944. Theory of Games and Economic Behavior. Science Editions, J. Wiley. 641 p.
6. Pospelov D.A. 1986. Situacionnoe upravlenie: Teorija I praktika. [Situational management: Theory and Practice]. Moscow: Nauka. 288 p.
7. Hubert K. Rampersad. 2005. Universal System Performance: How to achieve results while maintaining integrity, Wiley Publisher. 332 p.
8. Roizenson, G.V. Sinergeticheskij effect v prinyatii reshenij [Synergistic effect in decision making] // System research. Methodological problem. Yearbook / edited by V. Popkov, V. N. Sadovsky, V. I. Tishchenko. - №36. 2011-2012. M.: URSS, 2012. - P. 248-272.
9. Jay Wright Forrester. Industrial Dynamics. 2013. Martino Fine Books. 482 p.
10. Chereshkin D.S. Model processa prinyatiya reshenij v organizacionnoj sisteme [Model of decision-making in the organizational sysem] // Problemy sovremennoj nauki i obrazovaniya [Problems of modern science and education]. 2017. № 32 (114). S. 16-25.
11. John von Neumann. 1952. Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components. 98 p.
12. Britkov V.B., Roizenson G.V. 2016. Analiz bolshich dannych v patentnych issledovanijach. [Analysis of big data in the patent research]. The 15-th national conference on AI with international participation (KII-2016). Conference proceedings. – Vol. 1. – Smolensk: Universum. P. 291.
13. Galushkin A.I. 2000. Teorija neuronnych setej. [Theory of neural networks]. : Textbook for high schools / General editor A. I. Galushkin. – M.: IPGR. 416 p.
14. Popov E.V. 1987. Ekspertnye sistemy: Reshenie neformalizovannych zadach v dialoge z EVM [Expert systems: solving non-formalized problems in dialogue with computers]. M: Nauka. 288 p.
15. Kukushkin A.A. eds. 2014. Setecentricheskaya paradigma razvitiya situacionnyh centrov [Network-centric paradigm of development of situational centers]. Orel: Academy of the FGS of the Russian Federation. 163 p.
16. Marvin Minsky. 1974. A Framework for Representing Knowledge. MIT-AI Laboratory Memo 306, June, 1974. 76 p.
17. The representation and use of knowledge: translated from the Japanese. / ed. by H. Ueno, M. Ishizuka. 1989. Moscow: Mir. 220 p.
18. Nechetkie mnozhestva v modelyah upravleniya i iskusstvennom intellekte / pod red. D. A. Pospelova. 1986. [Fuzzy sets in management models and artificial intelligence / ed. by D. A. Pospelov]. Moscow: Nauka. 311 p.
19. Object Oriented Systems Analysis: Modeling the World in Data. 1988. Sally Shlaer, Stephen J. Mellor. Prentice Hall. 144 p.
20. Anfilatov V.S. et al. 2008. Sistemnyj analiz v upravlenii [System analysis in management] Studies Handbook / V. S. Anfilatov, A. A. Emelyanov,  A. A. Kukushkin, ed. by A. A. Emelyanov. Moscow: Finance and statistics. 368 p.
21. Larichev O.I., Moshkovich E.M. 1996. Kachestvennye metody prinjatija reshenij. [Qualitative methods of decision-making]. Moscow: Fizmatlit. 208 p.
22. Makarov B.M. 2011. Lekcii po veshchestvennomu analizu [Lectures on real analysis]: textbook. B. M. Makarov, A. N. Podkorytov. SPb.: BHV-Petersburg. 688 p.
23. Pavlov A.N., Sokolov B.V. 2006. Prinyatie reshenij v usloviyah nechetkoj informacii [Decision-Making in conditions of fuzzy information]. SPb: GUAP. 72 p.
24. Popkov Yu.S. 2013. Matematicheskaya demoekonomika. Makrosystemnyj podchod. [Mathematical demoeconomic. Macrosystem approach]. Moscow: LENAND. 560 p.
25. Alan Wilson. Entropy in Urban and Regional Modelling. Pion Limited. London. 1970. 166 p.
26. Tsygichko V.N. 1991. Rukovoditelyu – o prinyatii reshenij [To the head – about decisionmaking]. V. N. Tsygichko. Moscow: Finance and statistics. 240 p.
27. Gvardejcev M.I. et al. 1980. Specialnoe matematicheskoe obespechenie upravleniya [Special mathematical management software]. 2 ed. Moscow: Soviet radio. 536 p.
28. Kolmogorov A.N. 1965. Tri podhoda k opredeleniyu ponyatiya «kolichestvo informacii» [Three approaches to the definition of «quantity of information»]. //Problems of information transmission, 1965, volume 1, issue 1, From 3–11.
29. Chernoruckij I.G. 2005. Metody prinyatiya reshenij [Decision-making Methods]. SPb.: BHV-Petersburg. 416 p.
30. Vasilev F.P. 2011. Metody optimizacii. [Optimization Methods]. Moscow: MCNMO. 620 p.
31. Pavlov A.N., Sokolov B.V. 2006. Prinjatie reshenij v uslovijach nechetkoj informacii. [Decision making under fuzzy information]. GUAP. St.Petersburg. 72 p.
32. Vicenc Torra. 2014. When Mathematics goes to the Pools: Decision processes. RBA Collecionables S.A. 160 p.
33. Napravlenie fundamentalnyh issledovanij № 32 – Intellektualnye sistemy upravleniya; upravlenie znaniyami i sistemami mezhdisciplinarnoj prirody, chelovek v konture upravleniya. [Direction of fundamental research № 32 – Intellectual management systems; knowledge management and systems of interdisciplinary nature, man in the control loop]. Appendix № 2 To the program of fundamental research of the state academies of Sciences for 2013 – 2020 (as amended by the order of the Government of the Russian Federation of October 31, 2015 № 2217-p). P. 70.
34. Podinovskiy V.V. 2007. Vvedeniye v teoriyu vazhnosti kriteriyev v mnogokriterialnykh zadachakh prinyatiya resheniy. [Introduction to the theory of the importance of criteria in multi-criteria decision-making tasks]. Moscow: Fizmatlit. 64 p.
35. Metody opredeleniya koeffitsiyentov vazhnosti kriteriyev. [Methods for determining coefficients of importance of criteria] / A. M. Anokhin, V. A. Glotov, V. V. Pavelyev, A. M. Cherkashin // Avtomatika i telemekhanika. – 1997. – № 8. P. 3–35.
36. Glotov V.A. Pavelyev V. V. 1984. Vektornaya stratifikatsiya. [Vector stratification]. M.: Nauka. 94 p.
37. Shannon C.E. 1948. A Mathematical Theory of Communication, Bell System Technical Journal, 27, pp. 379–423 & 623–656, July & October.
38. Oskar Morgenstern. 1965. On the accuracy of economic observations. Second edition, completely revised. Princeton, New Jersey, Princeton University Press.
39. Puryaev A.S. 2006. Nauchnye osnovy ehkonomicheskih issledovanij [Scientific basis of economic research]. Textbook. Naberezhnye Chelny: KamPI. 182 p.
40. Morrow J.E. Open-Source Intelligence. Army Techniques Publication. No. 2-22.9 (FMI 2-22.9). Washington, DC, 10 July 2012. P.22. Available at: https://publicintelligence.net/fmi-2-22-9-open-source-intelligence (accessed 05.17.2018).
41. Imperiya chisel [Empire of numbers]. Available at: https://ru.numberempire.com/derivativecalculator.php (accessed March 12, 2018).
42. WolframAlpha computational knowledge engine. Available at: www.wolframalpha.com/examples/math/ (accessed February 27, 2018).
43. Borisov A.N. et al. 1989. Obrabotka nechetkoj informacii v sistemah prinyatiya reshenij [Processing of fuzzy information in decisionmaking systems]. Moscow: Radio i svyaz. 304 p.
 

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