Optimal forecast algorithm based on compatible linear filtration and extrapolation

dc.citation.epage167
dc.citation.issue2
dc.citation.spage157
dc.contributor.affiliationДержавна екологічна академія післядипломної освіти та менеджменту
dc.contributor.affiliationКиївський національний університет імені Тараса Шевченка
dc.contributor.affiliationState Ecological Academy of Postgraduate Education and Management
dc.contributor.affiliationTaras Shevchenko National University of Kyiv
dc.contributor.authorМашков, О. А.
dc.contributor.authorМурасов, Р. К.
dc.contributor.authorКравченко, Ю. В.
dc.contributor.authorДахно, Н. Б.
dc.contributor.authorЛещенко, О. О.
dc.contributor.authorТруш, О. В.
dc.contributor.authorMashkov, O. A.
dc.contributor.authorMurasov, R. K.
dc.contributor.authorKravchenko, Y. V.
dc.contributor.authorDakhno, N. B.
dc.contributor.authorLeschenko, O. A.
dc.contributor.authorTrush, A. V.
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-10-24T07:21:51Z
dc.date.available2023-10-24T07:21:51Z
dc.date.created2021-03-01
dc.date.issued2021-03-01
dc.description.abstractРозглянуто методи оптимальної лінійної екстраполяції траєкторії польоту літального апарату, що забезпечують мінімум середнього квадрату похибки прогнозу за різного обсягу апріорної інформації. В основу досліджень покладено канонічне розкладання векторного випадкового процесу. Визначається, що розвиток сучасних технологій тягне за собою підвищення вимог до якості та точності управління, але існуючі методи лінійної екстраполяції в зв’язку з властивими обмеженнями на випадковий процес, що описують рух літальних апаратів, не забезпечують максимальну точність прогнозу. Це робить необхідним подальший розвиток та удосконалення методів екстраполяції траєкторії літальних апаратів. Особливість розроблених методів екстраполяції траєкторії літальних апаратів полягає в тому, що дані методи в межах кореляційної моделі дозволяють повністю врахувати властивості реального випадкового процесу, що описує рух літального апарату на етапі заходу на посадку. У зв’язку з цим забезпечується максимально можлива точність лінійної екстраполяції за різноманітного стану інформаційного забезпечення. Розглянуті методи дозволяють підвищити безпеку польотів та ефективність застосування авіації. Це дає можливість розглядати нові можливості літальних апаратів та інших складних технічних систем.
dc.description.abstractThis work considers the methods of optimal linear extrapolation of the flight path of the aircraft, which provide a minimum of the mean square of the forecast error with different amounts of a priori information. The research is based on the canonical decomposition of a vectorial random process. It is determined that the development of modern technologies entails increasing requirements for quality and accuracy of control. However, since the existing methods of linear extrapolation do not provide for the maximum accuracy of the forecast due to the inherent constraints on the random process that describe the motion of aircraft, this necessitates a further development and improvement of methods for extrapolation of aircraft trajectories. The peculiarity of the developed methods for extrapolation of aircraft trajectory is that they allow within the correlation model to fully take into account the properties of a real random process that describes the motion of aircraft at the landing approach stage. This provides for the maximum possible accuracy of linear extrapolation with a variety of information support conditions. These methods allow improving the safety of flights and the efficiency of aviation. Accordingly, new capabilities of aircraft and other sophisticated technical systems can be further considered.
dc.format.extent157-167
dc.format.pages11
dc.identifier.citationOptimal forecast algorithm based on compatible linear filtration and extrapolation / O. A. Mashkov, R. K. Murasov, Y. V. Kravchenko, N. B. Dakhno, O. A. Leschenko, A. V. Trush // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2021. — Vol 8. — No 2. — P. 157–167.
dc.identifier.citationenOptimal forecast algorithm based on compatible linear filtration and extrapolation / O. A. Mashkov, R. K. Murasov, Y. V. Kravchenko, N. B. Dakhno, O. A. Leschenko, A. V. Trush // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2021. — Vol 8. — No 2. — P. 157–167.
dc.identifier.doidoi.org/10.23939/mmc2021.02.157
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/60390
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofMathematical Modeling and Computing, 2 (8), 2021
dc.relation.references[1] Zhengbing H., Mukhin V. Y., Kornaga Y. I., Herasymenko O. Y. Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components. Cybernetics and Systems Analysis. 53, 312–322 (2017).
dc.relation.references[2] Sushchenko O. A., Bezkorovayniy Y. M., Golytsin V. O. Processing of Redundant Information in Airborne Electronic Systems by means of Neural Networks. 2019 IEEE 39th International Conference on Electronics and Nanotechnology (ELNANO). 652–655 (2019).
dc.relation.references[3] Bezkorovainyi Y. N., Sushchenko O. A. Improvement of UAV Positioning by Information of Inertial Sensors. 2018 IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC). 123–126 (2018).
dc.relation.references[4] Barabash O., Lukova-Chuiko N., Sobchuk V., Musienko A. Application of Petri Networks for Support of Functional Stability of Information Systems. 2018 IEEE 1st International Conference on System Analysis and Intelligent Computing (SAIC). 1–4 (2018).
dc.relation.references[5] Mukhin V., Zavgorodnii V., Barabash O., Mykolaichuk R., Kornaga Y., Zavgorodnya A., Statkevych V. Method of restoring parameters of information objects in a unified information space based on computer networks. International Journal of Computer Network and Information Security. 12 (2), 11–21 (2020).
dc.relation.references[6] Obidin D., Ardelyan V., Lukova-Chuiko N., Musienko A. Estimation of functional stability of special purpose networks located on vehicles. 2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD). 167–170 (2017).
dc.relation.references[7] Grechko V., Babenko T., Myrutenko L. Secure Software Developing Recommendations. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T). 45–50 (2019).
dc.relation.references[8] Barabash O., Shevchenko H., Dakhno N., Kravchenko Y., Olga L. Effectiveness of Targeting Informational Technology Application. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 193–196 (2020).
dc.relation.references[9] Prats’ovytyi M., Svynchuk O. Spread of Values of a Cantor-Type Fractal Continuous Nonmonotone Function. J. Math. Sci. 240, 342–357 (2019).
dc.relation.references[10] Rokochinskiy A., Volk P., Kuzmych L., Turcheniuk V., Volk L., Dudnik A. Mathematical model of meteorological software for systematic flood control in the Carpathian region. 2019 IEEE International Conference on Advanced Trends in Information Theory ATIT. 143–148 (2019).
dc.relation.references[11] Hu Z., Mukhin V., Kornaga Y., Herasymenko O., Mostoviy Y. The Analytical Model for Distributed Computer System Parameters Control Based on Multi-factoring Estimations. Journal of Network and Systems Management. 27, 351–365 (2019).
dc.relation.references[12] Kravchenko Y., Leshchenko O., Dakhno N., Deinega V., Shevchenko H., Trush O. Intellectual fuzzy system air pollution control. 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT). 186–191 (2020).
dc.relation.references[13] Leshchenko O., Trush O., Dakhno N., Dudnik A., Kazintseva K., Kovalenko O. Methods for predicting adjustments to the rates of modern “digital money”. 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT). 222–226 (2020).
dc.relation.references[14] Hnatiienko H., Kudin V., Onyshchenko A., Snytyuk V., Kruhlov A. Greenhouse Gas Emission Determination Based on the Pseudo-Base Matrix Method for Environmental Pollution Quotas Between Countries Allocation Problem. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 1–8 (2020).
dc.relation.references[15] Barabash O. V., Open’ko P. V., Kopiika O. V., Shevchenko H. V., Dakhno N. B. Target programming with multicriterial restrictions application to the defense budget optimization. Advances in Military Technology. 14 (2), 213–229 (2019).
dc.relation.references[16] Kravchenko Y., Dakhno N., Leshchenko O., Tolstokorova A. Machine learning algorithms for predicting the results of COVID-19 coronavirus infection. CEUR Workshop Proceedings. 7th International Conference “Information Technology and Interactions”. 2845, 371–381 (2021).
dc.relation.references[17] Mashkov O. A., Sobchuk V. V., Barabash O. V., Dakhno N. B., Shevchenko H. V., Maisak T. V. Improvement of variational-gradient method in dynamical systems of automated control for integro-differential models. Mathematical Modeling and Computing. 6 (2), 344–357 (2019).
dc.relation.references[18] Barabash O. V., Musienko A. P., Sobchuk V. V., Lukova-Chuiko N. V., Svynchuk O. V. Distribution of Values of Cantor Type Fractal Functions with Specified Restrictions. Understanding Complex Systems. 433–455 (2021).
dc.relation.references[19] Tmienova N., Snytyuk V. Method of Deformed Stars for Global Optimization. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 1–4 (2020).
dc.relation.references[20] Zhengbing H., Mukhin V. Y., Kornaga Y. I., Herasymenko O. Y. Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components. Cybernetics and Systems Analysis. 53, 312–322 (2017).
dc.relation.references[21] Pysarchuk O., Gizun A., Dudnik A., Griga V., Domkiv T., Gnatyuk S. Bifurcation Prediction Method for the Emergence and Development Dynamics of Information Conflicts in Cybernetic Space. CEUR Workshop Proceedings. 2019 International Workshop on Cyber Hygiene. 2654, 692–709 (2020).
dc.relation.references[22] Kravchenko I. Yu. Forecasting mathematical model aircraft trajectory based on linear filtering and extrapolation stochastic process to mixed sequence its components. Information Processing Systems. 9 (116), 36–40 (2013).
dc.relation.references[23] Kudritsky V. D. Prediction of the reliability of electronic devices. Technics. 156 (1973).
dc.relation.references[24] Murasov R. K., Dziubenko Yu. A. Forecasting the state of complex systems in modern management systems and intelligent information systems. Collection of scientific works of Kyiv National University of Civil Engineering and Architecture. 7, 97–101 (2011).
dc.relation.references[25] Gramajo G., Shankar P. Efficient Energy Constraint Based UAV Path Planning for Search and Coverage. International Journal of Aerospace Engineering. 2017, Article ID 8085623, 13 pages (2017).
dc.relation.references[26] Mashkov O. A., Chumakevich V. A., Mamchur Yu. V., Kosenko V. R. The method of inverse problems of dynamics for the synthesis of a system of stabilization of the movement of a dynamic object on operatively programmable trajectories. Mathematical Modeling and Computing. 7 (1), 29–38 (2020).
dc.relation.references[27] Savchenko V., Haidur H., Gakhov S., Lehominova S., Muzshanova T., Novikova I. Model of control in a uav group for hidden transmitters detection on the basis of local self-organization. International Journal of Advanced Trends in Computer Science and Engineering. 9 (4), 6167–6174 (2020).
dc.relation.references[28] Guerriero F., Surace R., Loscr´ı V., Natalizio E. A multi-objective approach for unmanned aerial vehicle routing problem with soft time windows constraints. Applied Mathematical Modelling. 38 (3), 839–852 (2014).
dc.relation.referencesen[1] Zhengbing H., Mukhin V. Y., Kornaga Y. I., Herasymenko O. Y. Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components. Cybernetics and Systems Analysis. 53, 312–322 (2017).
dc.relation.referencesen[2] Sushchenko O. A., Bezkorovayniy Y. M., Golytsin V. O. Processing of Redundant Information in Airborne Electronic Systems by means of Neural Networks. 2019 IEEE 39th International Conference on Electronics and Nanotechnology (ELNANO). 652–655 (2019).
dc.relation.referencesen[3] Bezkorovainyi Y. N., Sushchenko O. A. Improvement of UAV Positioning by Information of Inertial Sensors. 2018 IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC). 123–126 (2018).
dc.relation.referencesen[4] Barabash O., Lukova-Chuiko N., Sobchuk V., Musienko A. Application of Petri Networks for Support of Functional Stability of Information Systems. 2018 IEEE 1st International Conference on System Analysis and Intelligent Computing (SAIC). 1–4 (2018).
dc.relation.referencesen[5] Mukhin V., Zavgorodnii V., Barabash O., Mykolaichuk R., Kornaga Y., Zavgorodnya A., Statkevych V. Method of restoring parameters of information objects in a unified information space based on computer networks. International Journal of Computer Network and Information Security. 12 (2), 11–21 (2020).
dc.relation.referencesen[6] Obidin D., Ardelyan V., Lukova-Chuiko N., Musienko A. Estimation of functional stability of special purpose networks located on vehicles. 2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD). 167–170 (2017).
dc.relation.referencesen[7] Grechko V., Babenko T., Myrutenko L. Secure Software Developing Recommendations. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T). 45–50 (2019).
dc.relation.referencesen[8] Barabash O., Shevchenko H., Dakhno N., Kravchenko Y., Olga L. Effectiveness of Targeting Informational Technology Application. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 193–196 (2020).
dc.relation.referencesen[9] Prats’ovytyi M., Svynchuk O. Spread of Values of a Cantor-Type Fractal Continuous Nonmonotone Function. J. Math. Sci. 240, 342–357 (2019).
dc.relation.referencesen[10] Rokochinskiy A., Volk P., Kuzmych L., Turcheniuk V., Volk L., Dudnik A. Mathematical model of meteorological software for systematic flood control in the Carpathian region. 2019 IEEE International Conference on Advanced Trends in Information Theory ATIT. 143–148 (2019).
dc.relation.referencesen[11] Hu Z., Mukhin V., Kornaga Y., Herasymenko O., Mostoviy Y. The Analytical Model for Distributed Computer System Parameters Control Based on Multi-factoring Estimations. Journal of Network and Systems Management. 27, 351–365 (2019).
dc.relation.referencesen[12] Kravchenko Y., Leshchenko O., Dakhno N., Deinega V., Shevchenko H., Trush O. Intellectual fuzzy system air pollution control. 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT). 186–191 (2020).
dc.relation.referencesen[13] Leshchenko O., Trush O., Dakhno N., Dudnik A., Kazintseva K., Kovalenko O. Methods for predicting adjustments to the rates of modern "digital money". 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT). 222–226 (2020).
dc.relation.referencesen[14] Hnatiienko H., Kudin V., Onyshchenko A., Snytyuk V., Kruhlov A. Greenhouse Gas Emission Determination Based on the Pseudo-Base Matrix Method for Environmental Pollution Quotas Between Countries Allocation Problem. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 1–8 (2020).
dc.relation.referencesen[15] Barabash O. V., Open’ko P. V., Kopiika O. V., Shevchenko H. V., Dakhno N. B. Target programming with multicriterial restrictions application to the defense budget optimization. Advances in Military Technology. 14 (2), 213–229 (2019).
dc.relation.referencesen[16] Kravchenko Y., Dakhno N., Leshchenko O., Tolstokorova A. Machine learning algorithms for predicting the results of COVID-19 coronavirus infection. CEUR Workshop Proceedings. 7th International Conference "Information Technology and Interactions". 2845, 371–381 (2021).
dc.relation.referencesen[17] Mashkov O. A., Sobchuk V. V., Barabash O. V., Dakhno N. B., Shevchenko H. V., Maisak T. V. Improvement of variational-gradient method in dynamical systems of automated control for integro-differential models. Mathematical Modeling and Computing. 6 (2), 344–357 (2019).
dc.relation.referencesen[18] Barabash O. V., Musienko A. P., Sobchuk V. V., Lukova-Chuiko N. V., Svynchuk O. V. Distribution of Values of Cantor Type Fractal Functions with Specified Restrictions. Understanding Complex Systems. 433–455 (2021).
dc.relation.referencesen[19] Tmienova N., Snytyuk V. Method of Deformed Stars for Global Optimization. 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). 1–4 (2020).
dc.relation.referencesen[20] Zhengbing H., Mukhin V. Y., Kornaga Y. I., Herasymenko O. Y. Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components. Cybernetics and Systems Analysis. 53, 312–322 (2017).
dc.relation.referencesen[21] Pysarchuk O., Gizun A., Dudnik A., Griga V., Domkiv T., Gnatyuk S. Bifurcation Prediction Method for the Emergence and Development Dynamics of Information Conflicts in Cybernetic Space. CEUR Workshop Proceedings. 2019 International Workshop on Cyber Hygiene. 2654, 692–709 (2020).
dc.relation.referencesen[22] Kravchenko I. Yu. Forecasting mathematical model aircraft trajectory based on linear filtering and extrapolation stochastic process to mixed sequence its components. Information Processing Systems. 9 (116), 36–40 (2013).
dc.relation.referencesen[23] Kudritsky V. D. Prediction of the reliability of electronic devices. Technics. 156 (1973).
dc.relation.referencesen[24] Murasov R. K., Dziubenko Yu. A. Forecasting the state of complex systems in modern management systems and intelligent information systems. Collection of scientific works of Kyiv National University of Civil Engineering and Architecture. 7, 97–101 (2011).
dc.relation.referencesen[25] Gramajo G., Shankar P. Efficient Energy Constraint Based UAV Path Planning for Search and Coverage. International Journal of Aerospace Engineering. 2017, Article ID 8085623, 13 pages (2017).
dc.relation.referencesen[26] Mashkov O. A., Chumakevich V. A., Mamchur Yu. V., Kosenko V. R. The method of inverse problems of dynamics for the synthesis of a system of stabilization of the movement of a dynamic object on operatively programmable trajectories. Mathematical Modeling and Computing. 7 (1), 29–38 (2020).
dc.relation.referencesen[27] Savchenko V., Haidur H., Gakhov S., Lehominova S., Muzshanova T., Novikova I. Model of control in a uav group for hidden transmitters detection on the basis of local self-organization. International Journal of Advanced Trends in Computer Science and Engineering. 9 (4), 6167–6174 (2020).
dc.relation.referencesen[28] Guerriero F., Surace R., Loscr´ı V., Natalizio E. A multi-objective approach for unmanned aerial vehicle routing problem with soft time windows constraints. Applied Mathematical Modelling. 38 (3), 839–852 (2014).
dc.rights.holder© Національний університет “Львівська політехніка”, 2021
dc.subjectканонічний розклад випадкового процесу
dc.subjectпрогнозування випадкових процесів
dc.subjectметод спільної лінійної фільтрації та екстраполяції
dc.subjectоптимальний метод узгодженої екстраполяції
dc.subjectcanonical decomposition of random process
dc.subjectrandom process forecast
dc.subjectjoint linear filtration and extrapolation method
dc.subjectoptimal method of consistent extrapolation
dc.titleOptimal forecast algorithm based on compatible linear filtration and extrapolation
dc.title.alternativeОптимальний алгоритм прогнозу на основі сумісної лінійної фільтрації та екстраполяції
dc.typeArticle

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