[[1] Agapova A., Madura J., Market uncertainty and earnings guidance, The Quarterly Review of Economics and Finance, 61, 2016, 97–111.10.1016/j.qref.2015.12.001]Search in Google Scholar
[[2] Alhassan E., Sjostrand H., Helgesson P., Osterlund M., Pomp S., Koning A. J., Rochman D., On the use of integral experiments for uncertainty reduction of reactor macroscopic parameters within the TMC methodology, Progress in Nuclear Energy, 88, 2016, 43–52.10.1016/j.pnucene.2015.11.015]Search in Google Scholar
[[3] Bazerman M. H., Moore D. A., Judgment in Managerial Decision Making (8th ed.), Wiley, River Street, Hoboken, NJ, 2013.]Search in Google Scholar
[[4] Betzler N., Fellows M. R., Guo J., Niedermeier R., Rosamond F. A., Fixed-parameter algorithms for Kemeny rankings, Theoretical Computer Science, 410 (45), 2009, 4554–4570.10.1016/j.tcs.2009.08.033]Search in Google Scholar
[[5] Blalock H. M., Social Statistics, McGraw-Hill, New York, NY, 1979.]Search in Google Scholar
[[6] Branke J., Deb K., Miettinen K., Słowiński R. (eds.), Multiobjective Optimization: Interactive and Evolutionary Approaches (Lecture Notes in Computer Science (5252), Springer, Berlin, 2008.]Search in Google Scholar
[[7] Ghashim E., Marchand E., Strawderman W. E., On a better lower bound for the frequentist probability of coverage of Bayesian credible intervals in restricted parameter spaces, Statistical Methodology, 31, 2016, 43–57.10.1016/j.stamet.2016.01.006]Search in Google Scholar
[[8] Goodwin G. C., Payne R. L., Dynamic System Identification: Experiment Design and Data Analysis, Academic Press, New York, NY, 1977.]Search in Google Scholar
[[9] Guo P., Tanaka H., Decision making with interval probabilities, European Journal of Operational Research, 203 (2), 2010, 444–454.10.1016/j.ejor.2009.07.020]Search in Google Scholar
[[10] Han Y., Liu W., Bretz F., Wan F., Yang P., Statistical calibration and exact one-sided simultaneous tolerance intervals for polynomial regression, Journal of Statistical Planning and Inference, 168, 2016, 90-96.10.1016/j.jspi.2015.07.005]Search in Google Scholar
[[11] Harris I. R., A simple approximation to the likelihood interval for a binomial proportion, Statistical Methodology, 13, 2013, 42–47.10.1016/j.stamet.2013.01.005]Search in Google Scholar
[[12] Haykin S., Neural Networks: A Comprehensive Foundation, Prentice Hall, Upper Saddle River, NJ, 1999.]Search in Google Scholar
[[13] Jablonski A., Barszcz T., Bielecka M., Breuhaus P., Modeling of probability distribution functions for automatic threshold calculation in condition monitoring systems, Measurement, 46 (1), 2013, 727–738.10.1016/j.measurement.2012.09.011]Search in Google Scholar
[[14] Kangin D., Kolev G., Vikhoreva A., Further parameters estimation of neocognitron neural network modification with FFT convolution, Journal of Telecommunication, Electronic and Computer Engineering, 4 (2), 2012, 21–26.]Search in Google Scholar
[[15] Lan Y., Liu Y. K., Sun G., Modeling fuzzy multi-period production planning and sourcing problem with credibility service levels, Journal of Computational and Applied Mathematics, 231 (1), 2009, 208–221.10.1016/j.cam.2009.02.009]Search in Google Scholar
[[16] Lehmann E. L., Casella G., Theory of Point Estimation (2nd ed.), Springer, New York, NY, 1998.]Search in Google Scholar
[[17] Lequy E., Sauvage S., Laffray X., Gombert-Courvoisier S., Pascaud A., Galsomies L., Leblond S., Assessment of the uncertainty of trace metal and nitrogen concentrations in mosses due to sampling, sample preparation and chemical analysis based on the French contribution to ICP-Vegetation, Ecological Indicators, 71, 2016, 20–31.10.1016/j.ecolind.2016.06.046]Search in Google Scholar
[[18] Li X., Qin Z., Interval portfolio selection models within the framework of uncertainty theory, Economic Modelling, 41, 2014, 338–344.10.1016/j.econmod.2014.05.036]Search in Google Scholar
[[19] Li Y. P., Huang G. H., Nie S. L., A robust interval-based minimax-regret analysis approach for the identification of optimal water-resources-allocation strategies under uncertainty, Resources, Conservation and Recycling, 54 (2), 2009, 86–96.10.1016/j.resconrec.2009.06.011]Search in Google Scholar
[[20] Liebowitz J., The Handbook of Applied Expert Systems, CRC Press, Boca Raton, FL, 1997.]Search in Google Scholar
[[21] Liu Z., Fan S., Wang H. J., Zhao J. L., Enabling effective workflow model reuse: A data-centric approach, Decision Support Systems, 93, 2017, 11–25.10.1016/j.dss.2016.09.002]Search in Google Scholar
[[22] Manly B. F. J., Statistics for Environmental Science and Management, Chapman & Hall/CRC, Boca Raton, FL, 2008.]Search in Google Scholar
[[23] Menendez P., Fan Y., Garthwaite P. H., Sisson S. A., Simultaneous adjustment of bias and coverage probabilities for confidence intervals, Computational Statistics & Data Analysis, 70, 2014, 35–44.10.1016/j.csda.2013.08.016]Search in Google Scholar
[[24] Muscolino G., Santoro R., Sofi A., Reliability analysis of structures with interval uncertainties under stationary stochastic excitations, Computer Methods in Applied Mechanics and Engineering, 300, 2016, 47–69.10.1016/j.cma.2015.10.023]Search in Google Scholar
[[25] Nott D. J., Marshall L., Fielding M., Liong S.-Y., Mixtures of experts for understanding model discrepancy in dynamic computer models, Computational Statistics & Data Analysis, 71, 2014, 491–505.10.1016/j.csda.2013.04.020]Search in Google Scholar
[[26] Pan L., Politis D. N., Bootstrap prediction intervals for Markov processes, Computational Statistics & Data Analysis, 100, 2016, 467–494.10.1016/j.csda.2015.05.010]Search in Google Scholar
[[27] Parmigiani G., Inoue L., Decision Theory: Principles and Approaches, Wiley, Chichester, UK, 2009.10.1002/9780470746684]Search in Google Scholar
[[28] Pasquier R., Smith I. F. C., Robust system identification and model predictions in the presence of systematic uncertainty, Advanced Engineering Informatics, 29 (4), 2015, 1096-1109.10.1016/j.aei.2015.07.007]Search in Google Scholar
[[29] Pham H. V., Tsai F. T.-C., Bayesian experimental design for identification of model propositions and conceptual model uncertainty reduction, Advances in Water Resources, 83, 2015, 148-159.10.1016/j.advwatres.2015.05.024]Search in Google Scholar
[[30] Pinedo M. L., Scheduling: Theory, Algorithms, and Systems, Springer, 2016.]Search in Google Scholar
[[31] Qin R., Liu Y. K., Liu Z., Modeling fuzzy data envelopment analysis by parametric programming method, Expert Systems with Applications, 38 (7), 2011, 8648-8663.10.1016/j.eswa.2011.01.071]Search in Google Scholar
[[32] Rajabi M. M., Ataie-Ashtiani B., Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation, Journal of Hydrology, 536, 2016, 255-272.10.1016/j.jhydrol.2016.02.029]Search in Google Scholar
[[33] Revesz P., Birnbaum Z. W., Lukacs E., The Laws of Large Numbers, Academic Press, New York, NY, London, England, 1968.]Search in Google Scholar
[[34] Romanuke V. V., Environment guard model as dyadic three-person game with the generalized fine for the reservoir pollution, Ecological Safety and Nature Management, 6, 2010, 77–94.]Search in Google Scholar
[[35] Romanuke V. V., Theoretic-game methods of identification of models for multistage technical control and run-in under multivariate uncertainties (a Dissertation for the Doctoral Degree of Technical Sciences in Speciality 01.05.02 Mathematical Modeling and Computational Methods), Vinnytsia National Technical University, Vinnytsia, Ukraine, 2014 (in Ukrainian).]Search in Google Scholar
[[36] Romanuke V. V., Uniform sampling of fundamental simplexes as sets of players’ mixed strategies in the finite noncooperative game for finding equilibrium situations with possible concessions, Journal of Automation and Information Sciences, 47 (9), 2015, 76–85.10.1615/JAutomatInfScien.v47.i9.70]Search in Google Scholar
[[37] Romanuke V. V., Algorithm of fast Kemeny consensus by searching over standard matrices distanced to the first ranking as the averaged expert ranking by minimal difference, Research Bulletin of NTUU “Kyiv Polytechnic Institute”, 1, 2016, 50–57.10.20535/1810-0546.2016.1.59784]Search in Google Scholar
[[38] Romanuke V. V., Multiple state problem reduction and decision making criteria hybridization, Research Bulletin of NTUU “Kyiv Polytechnic Institute”, 2, 2016, 51–59.10.20535/1810-0546.2016.2.61603]Search in Google Scholar
[[39] Romanuke V. V., Adjustment of a positive integer parameter unknown to an interval with constant boundaries based on expert estimations whose average-like value is upper-limited to the parameter, Herald of Khmelnytskyi national university. Technical sciences, 4, 2016, 116–123.]Search in Google Scholar
[[40] Romanuke V. V., Hard and soft adjusting of a parameter with its known boundaries by the value based on the experts’ estimations limited to the parameter, Electrical, Control and Communication Engineering, 10, 2016, 23–28.10.1515/ecce-2016-0003]Search in Google Scholar
[[41] Romanuke V. V., Evaluation of payoff matrices for noncooperative games via processing binary expert estimations, Information Technology and Management Science, 19, 2016, 10–15.10.1515/itms-2016-0004]Search in Google Scholar
[[42] Romanuke V. V., Interval uncertainty reduction via division-by-2 dichotomization based on expert estimations for short-termed observations, Journal of Uncertain Systems, 12 (1), 2018, 3–21.]Search in Google Scholar
[[43] Sofi A., Romeo E., A novel Interval Finite Element Method based on the improved interval analysis, Computer Methods in Applied Mechanics and Engineering, 311, 2016, 671–697.10.1016/j.cma.2016.09.009]Search in Google Scholar
[[44] Walpole R. E., Myers R. H., Myers S. L., Ye K., Probability & Statistics for Engineers & Scientists (9th ed.), Prentice Hall, Boston, MA, 2012.]Search in Google Scholar
[[45] Walter E., Pronzato L., Identification of Parametric Models from Experimental Data. Springer, London, UK, 1997.]Search in Google Scholar
[[46] Wang M., Huang Q., A new hybrid uncertain analysis method for structural-acoustic systems with random and interval parameters, Computers & Structures, 175, 2016, 15-28.10.1016/j.compstruc.2016.07.001]Search in Google Scholar
[[47] Xia M., Cai C. S., Pan F., Yu Y., Estimation of extreme structural response distributions for mean recurrence intervals based on short-term monitoring, Engineering Structures, 126, 2016, 121-132.10.1016/j.engstruct.2016.07.052]Search in Google Scholar
[[48] Young P., Zamir S. (eds.), Handbook of Game Theory. Volume 4, North Holland, 2015.]Search in Google Scholar
[[49] Zaman K., Rangavajhala S., McDonald M. P., Mahadevan S., A probabilistic approach for representation of interval uncertainty, Reliability Engineering & System Safety, 96 (1), 2011, 117-130.10.1016/j.ress.2010.07.012]Search in Google Scholar
[[50] Zhou Y., Fenton N., Neil M., Bayesian network approach to multinomial parameter learning using data and expert judgments, International Journal of Approximate Reasoning, 55 (5), 2014, 1252-1268.10.1016/j.ijar.2014.02.008]Search in Google Scholar