Investigating errors when forecasting processes with uncertain dynamics and observation noise by the self-adjusting brown's zero-order model
Keywords:forecasting errors, self-adjusting Brown's zero-order model, process dynamics uncertainty
This paper reports a study into the errors of process forecasting under the conditions of uncertainty in the dynamics and observation noise using a self-adjusting Brown's zero-order model. The dynamics test models have been built for predicted processes and observation noises, which make it possible to investigate forecasting errors for the self-adjusting and adaptive models. The test process dynamics were determined in the form of a rectangular video pulse with a fixed unit amplitude, a radio pulse of the harmonic process with an amplitude attenuated exponentially, as well as a video pulse with amplitude increasing exponentially. As a model of observation noise, an additive discrete Gaussian process with zero mean and variable value of the mean square deviation was considered. It was established that for small values of the mean square deviation of observation noise, a self-adjusting model under the conditions of dynamics uncertainty produces a smaller error in the process forecast. For the test jump-like dynamics of the process, the variance of the forecast error was less than 1 %. At the same time, for the adaptive model, with an adaptation parameter from the classical and beyond-the-limit sets, the variance of the error was about 20 % and 5 %, respectively. With significant observation noises, the variance of the error in the forecast of the test process dynamics for the self-adjusting and adaptive models with a parameter from the classical set was in the range from 1 % to 20 %. However, for the adaptive model, with a parameter from the beyond-the-limit set, the variance of the prediction error was close to 100 % for all test models. It was established that with an increase in the mean square deviation of observation noise, there is greater masking of the predicted test process dynamics, leading to an increase in the variance of the forecast error when using a self-adjusting model. This is the price for predicting processes with uncertain dynamics and observation noises.
- Vambol, S., Vambol, V., Bogdanov, I., Suchikova, Y., Rashkevich, N. (2017). Research of the influence of decomposition of wastes of polymers with nano inclusions on the atmosphere. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 57–64. doi: https://doi.org/10.15587/1729-4061.2017.118213
- Semko, A., Rusanova, O., Kazak, O., Beskrovnaya, M., Vinogradov, S., Gricina, I. (2015). The use of pulsed high-speed liquid jet for putting out gas blow-out. The International Journal of Multiphysics, 9 (1), 9–20. doi: https://doi.org/10.1260/1750-95188.8.131.52
- Migalenko, K., Nuianzin, V., Zemlianskyi, A., Dominik, A., Pozdieiev, S. (2018). Development of the technique for restricting the propagation of fire in natural peat ecosystems. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 31–37. doi: https://doi.org/10.15587/1729-4061.2018.121727
- Vambol, S., Vambol, V., Sobyna, V., Koloskov, V., Poberezhna, L. (2019). Investigation of the energy efficiency of waste utilization technology, with considering the use of low-temperature separation of the resulting gas mixtures. Energetika, 64 (4). doi: https://doi.org/10.6001/energetika.v64i4.3893
- Semko, A. N., Beskrovnaya, M. V., Vinogradov, S. A., Hritsina, I. N., Yagudina, N. I. (2014). The usage of high speed impulse liquid jets for putting out gas blowouts. Journal of Theoretical and Applied Mechanics, 52 (3), 655–664.
- Kovalov, A., Otrosh, Y., Ostroverkh, O., Hrushovinchuk, O., Savchenko, O. (2018). Fire resistance evaluation of reinforced concrete floors with fire-retardant coating by calculation and experimental method. E3S Web of Conferences, 60, 00003. doi: https://doi.org/10.1051/e3sconf/20186000003
- Otrosh, Y., Semkiv, O., Rybka, E., Kovalov, A. (2019). About need of calculations for the steel framework building in temperature influences conditions. IOP Conference Series: Materials Science and Engineering, 708, 012065. doi: https://doi.org/10.1088/1757-899x/708/1/012065
- Vambol, S., Vambol, V., Kondratenko, O., Suchikova, Y., Hurenko, O. (2017). Assessment of improvement of ecological safety of power plants by arranging the system of pollutant neutralization. Eastern-European Journal of Enterprise Technologies, 3 (10 (87)), 63–73. doi: https://doi.org/10.15587/1729-4061.2017.102314
- Dadashov, I., Loboichenko, V., Kireev, A. (2018). Analysis of the ecological characteristics of environment friendly fire fighting chemicals used in extinguishing oil products. Pollution Research, 37 (1), 63–77.
- Lukashin, Yu. P. (2003). Adaptivnye metody kratkosrochnogo prognozirovaniya vremennykh ryadov. Moscow: Finansy i statistika, 416.
- Brown, R. G. (2004). Smoothing, forecasting and prediction of discrete time series. Dover Publications, 480.
- Chetyrkin, E. M. (1977). Statisticheskie metody prognozirovaniya. Moscow: Statistika, 200.
- Lugachev, M. I., Lyapuncov, Yu. P. (1999). Metody social'no-ekonomicheskogo prognozirovaniya. Moscow: TEIS, 160.
- Svetun'kov, S. G. (2002). O rasshirenii granic primeneniya metoda Brauna. Izvestiya SPGUEF, 3, 94–107.
- Vartanyan, V. M., Romanenkov, Yu. A., Kononenko, A. V. (2005). Parametricheskiy sintez prognoznoy modeli eksponencial'nogo sglazhivaniya. Vestnik NTU «KhPI», 59, 9–16. Available at: http://repository.kpi.kharkov.ua/bitstream/KhPI-Press/28135/1/vestnik_KhPI_2005_59_Vartanyan_Parametricheskiy.pdf
- Tebueva, F., Streblianskaia, N. (2016). Adaptive method for predicting short time series of natural processes. Sovremennaya nauka: aktual'nye problemy teorii i praktiki, 6, 83–87. Available at: http://nauteh-journal.ru/files/eb917d86-88f4-4395-b12c-08b45ff3fbbb
- Svetun'kov, I. S. (2010). Samoobuchayuschayasya model' kratkosrochnogo prognozirovaniya social'no-ekonomicheskoy dinamiki. Modeli ocenki, analiza i prognozirovaniya social'no-ekonomicheskikh sistem. Kharkiv: INZhEK, 11–32. Available at: https://publications.hse.ru/mirror/pubs/share/folder/q1zrwhrj6z/direct/84096936.pdf
- Koshmarov, Yu. A., Puzach, S. V., Andreev, V. V. (2012). Prognozirovanie opasnykh faktorov pozhara v pomeschenii. Moscow: AGPS MCHS Rossii, 126.
- Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Borodych, P. (2018). Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises. Eastern-European Journal of Enterprise Technologies, 3 (9 (93)), 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127
- Webber,, C. L., Ioana, C., Marwan, N. (Eds.). (2016). Recurrence Plots and Their Quantifications: Expanding Horizons. Springer Proceedings in Physics. doi: https://doi.org/10.1007/978-3-319-29922-8
- Ahn, C.-S., Kim J.-Y. (2011). A study for a fire spread mechanism of residential buildings with numerical modeling. WIT Transactions on the Built Environment, 117 (12), 185–196. doi: https://doi.org/10.2495/safe110171
- Sadkovyi, V., Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Rud, A. et. al. (2020). Construction of a method for detecting arbitrary hazard pollutants in the atmospheric air based on the structural function of the current pollutant concentrations. Eastern-European Journal of Enterprise Technologies, 6 (10 (108)), 14–22. doi: https://doi.org/10.15587/1729-4061.2020.218714
- Poulsen, A., Jomaas, G. (2011). Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings. Fire Technology, 48 (2), 419–439. doi: https://doi.org/10.1007/s10694-011-0230-0
- Zhang, D., Xue, W. (2010). Effect of heat radiation on combustion heat release rate of larch. Journal of West China Forestry Science, 39, 148.
- Peng, X., Liu, S., Lu, G. (2005). Experimental analysis on heat release rate of materials. Journal of Chongqing University, 28, 122.
- ndronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694
- Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5 (10 (95)), 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995
- Pospelov, B., Rybka, E., Meleshchenko, R., Gornostal, S., Shcherbak, S. (2017). Results of experimental research into correlations between hazardous factors of ignition of materials in premises. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 50–56. doi: https://doi.org/10.15587/1729-4061.2017.117789
- Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons. doi: https://doi.org/10.1002/9781118032428
- Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL, 1–7. Available at: https://hal.archives-ouvertes.fr/hal-01303330
- Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, Amazon, 655.
- Giv, H. H. (2013). Directional short-time Fourier transform. Journal of Mathematical Analysis and Applications, 399 (1), 100–107. doi: https://doi.org/10.1016/j.jmaa.2012.09.053
- Pospelov, B., Andronov, V., Rybka, E., Popov, V., Semkiv, O. (2018). Development of the method of frequencytemporal representation of fluctuations of gaseous medium parameters at fire. Eastern-European Journal of Enterprise Technologies, 2 (10 (92), 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926
- Pospelov, B., Andronov, V., Rybka, E., Samoilov, M., Krainiukov, O., Biryukov, I. et. al. (2021). Development of the method of operational forecasting of fire in the premises of objects under real conditions. Eastern-European Journal of Enterprise Technologies, 2 (10 (110)), 43–50. doi: https://doi.org/10.15587/1729-4061.2021.226692
- Sinaga, H., Irawati, N. (2020). A Medical Disposable Supply Demand Forecasting By Moving Average And Exponential Smoothing Method. Proceedings of the Proceedings of the 2nd Workshop on Multidisciplinary and Applications (WMA) 2018, 24-25 January 2018, Padang, Indonesia. doi: https://doi.org/10.4108/eai.24-1-2018.2292378
- Pospelov, B., Rybka, E., Meleshchenko, R., Borodych, P., Gornostal, S. (2019). Development of the method for rapid detection of hazardous atmospheric pollution of cities with the help of recurrence measures. Eastern-European Journal of Enterprise Technologies, 1 (10 (97)), 29–35. doi: https://doi.org/10.15587/1729-4061.2019.155027
- Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Harbuz, S., Bezuhla, Y. et. al. (2020). Use of uncertainty function for identification of hazardous states of atmospheric pollution vector. Eastern-European Journal of Enterprise Technologies, 2 (10 (104)), 6–12. doi: https://doi.org/10.15587/1729-4061.2020.200140
- Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Biryukov, I., Butenko, T. et. al. (2021). Short-term fire forecast based on air state gain recurrence and zero-order brown model. Eastern-European Journal of Enterprise Technologies, 3 (10 (111)), 27–33. doi: https://doi.org/10.15587/1729-4061.2021.233606
- Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Maksymenko, N., Biryukov, I. et. al. (2021). Devising a self-adjusting zero-order Brown’s model for predicting irreversible processes and phenomena. Eastern-European Journal of Enterprise Technologies, 5 (10 (113), 40–47. doi: https://doi.org/10.15587/1729-4061.2021.241474
- Pospelov, B., Rybka, E., Krainiukov, O., Yashchenko, O., Bezuhla, Y., Bielai, S. et. al. (2021). Short-term forecast of fire in the premises based on modification of the Brown’s zero-order model. Eastern-European Journal of Enterprise Technologies, 4 (10 (112)), 52–58. doi: https://doi.org/10.15587/1729-4061.2021.238555
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Copyright (c) 2021 Boris Pospelov, Evgenіy Rybka, Mikhail Samoilov, Olekcii Krainiukov, Yurii Kulbachko, Yuliia Bezuhla, Oleksii Roianov, Svitlana Hryshko, Ivetta Krivitska, Valentyna Ivanova
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