Control of Mathematical Modeling Process of Dynamics of Harmful Substances Concentrations on the Basis of Ontological Approach

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dc.citation.epage16
dc.citation.issue1
dc.citation.spage7
dc.contributor.affiliationWest Ukrainian National University, Ternopil, Ukraine
dc.contributor.affiliationUniversity of South Bohemia, Czech Republic
dc.contributor.authorДивак, Микола
dc.contributor.authorМельник, Андрій
dc.contributor.authorПукас, Андрій
dc.contributor.authorДосталек, Лібор
dc.contributor.authorDyvak, Mykola
dc.contributor.authorMelnyk, Andriy
dc.contributor.authorPukas, Andriy
dc.contributor.authorDostalek, Libor
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-04-26T09:41:14Z
dc.date.available2023-04-26T09:41:14Z
dc.date.created2022-04-04
dc.date.issued2022-04-04
dc.description.abstractРозглянуто проблему побудови математичної моделі динаміки концентрацій діоксиду азоту на різних ділянках міста, особливості побудови таких моделей на основі періодичного вимірювання концентрацій шкідливих речовин та ідентифікації на підставі отриманих вимірювань. У статті також запропоновано онтологічний підхід як інструмент управління, що дає змогу значно спростити систематичні стандартизовані методи зберігання моделей, процес їх побудови та відповідного використання у практичних ситуаціях. Використання онтологічної моделі дає змогу формалізувати процес отримання, зберігання та використання відповідних знань та підходить для інтелектуалізованіших систем, забезпечує визначення завідомо хибних розв’язків на основі моделі, прогнозного контролю моделі, оптимізації процесу прийняття рішень на основі знань та моделювання відповідної технологічної схеми. Описано також особливості побудови відповідної онтологічної моделі, схему вибору нелінійної моделі з “перемиканнями” на різні умови. В роботі висвітлено також відповідні експериментальні дослідження, які дають змогу підтвердити ефективність запропонованого підходу.
dc.description.abstractThe problem of building a mathematical model of the dynamics of nitrogen dioxide concentrations at different parts of the city is considered in the paper. The peculiarities of the construction of such models on the basis of periodic measurement of concentrations of harmful substances and identification on the basis of the measurements obtained are considered. This paper also proposes an ontological approach as a control tool that greatly simplifies the systematic standardized methods of the models storage, the process of their construction and appropriate usage in practice. The use of the ontological model allows formalizing the process of obtaining, storing and using relevant knowledge and is suitable for more intelligent systems, such as identification of obviously erroneous solutions based on the model, predictive control of the model, optimization of the decision-making process based on knowledge and modeling of an appropriate technological flow chart. This paper also describes the features of the construction of the corresponding ontological model, the pattern of choice of a nonlinear model with “switching” to different conditions. Relevant experimental studies have also been conducted to confirm the effectiveness of the proposed approach.
dc.format.extent7-16
dc.format.pages10
dc.identifier.citationControl of Mathematical Modeling Process of Dynamics of Harmful Substances Concentrations on the Basis of Ontological Approach / Mykola Dyvak, Andriy Melnyk, Andriy Pukas, Libor Dostalek // Computational Problems of Electrical Engineering. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 12. — No 1. — P. 7–16.
dc.identifier.citationenDyvak M., Melnyk A., Pukas A., Dostalek L. (2022) Control of Mathematical Modeling Process of Dynamics of Harmful Substances Concentrations on the Basis of Ontological Approach. Computational Problems of Electrical Engineering (Lviv), vol. 12, no 1, pp. 7-16.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/58472
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofComputational Problems of Electrical Engineering, 1 (12), 2022
dc.relation.references[1] M. Dyvak, N. Porplytsya, and Y. Maslyiak, “Modified Method of Structural Identification of Interval Discrete Models of Atmospheric Pollution by Harmful Emissions from Motor Vehicles”, in Proc. Advances in Intelligent Systems and Computing IV. CSIT 2019, vol. 1080. Springer, Cham. 2020. https://doi.org/ 10.1007/978-3-030-33695-0_33.
dc.relation.references[2] M. Dyvak, N. Porplytsya; and I. Borivets, and M. Shynkaryk, “Improving the computational implementation of the parametric identification method for interval discrete dynamic models”. in Proc. 12th International Scientific and Technical Conference on Computer Science and Information Technologies (CSIT), Lviv, Ukraine, 5–8 September 2017; pp. 533–536, DOI: 10.1109 / STCCSIT.2017.809884
dc.relation.references[3] M. Dyvak, Y. Maslyiak and A. Pukas, “Information Technology for Modeling of Atmosphere Pollution Processes by Motor Vehicle Harmful Emissions”, in Proc. IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), pp. 1–5, 2019. DOI: 10.1109 / CADSM.2019.8779268.
dc.relation.references[4] Mykola Dyvak, Parameters Identification Method of Interval Discrete Dynamic Models of Air Pollution Based on Artificial Bee Colony Algorithm, 2020, 130–135. 10.1109/ACIT49673.2020.9208972
dc.relation.references[5] N. Ocheretnyuk, I. Voytyuk, M. Dyvak, and Ye. Martsenyuk, “Features of structure identification the macromodels for nonsta-tionary fields of air pollution from vehicles”. in Proc. Modern Problems of Radio Engineering, Telecommunications and Computer Science, Proceedings of the 11th International Conference, Lviv, Ukraine, p. 444, 17–19 May, 2012.
dc.relation.references[6] M. Dyvak, Y. Maslyiak and A. Pukas, “Information Technology for Modeling of Atmosphere Pollution Processes by Motor Vehicle Harmful Emissions”, in Proc. IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), pp. 1–5, 2019. DOI: 10.1109 / CADSM.2019.8779268.
dc.relation.references[7] Munira Mohd Ali, Ruoyu Yang, Binbin Zhang, Francesco Furini, Rahul Rai, J. Neil Otte, and Barry Smith, “Enriching the functionally graded materials (FGM) ontology for digital manufacturing”, International Journal of Production Research 0: 0, pp. 1–18, 2020.
dc.relation.references[8] Suresh, P., G. Joglekar, Shuo-Huan Hsu, P. Akkisetty, Leaelaf Hailemariam, Ankur Jain, G. Reklaitis and V. Venkatasubramanian. “Onto MODEL: Ontological mathematical modeling knowledge management”. Computer-aided chemical engineering, no. 25, pp. 985–990, 2008.
dc.relation.references[9] Trokanas, Nikolaos and F. Cecelja. “Ontology evaluation for reuse in the domain of Process Systems Engineering”. Comput. Chem. Eng. no. 85, pp. 177–187, 2016.
dc.relation.references[10]Yang, Lan, K. Cormican and Ming Yu. “Ontology Learning for Systems Engineering Body of Knowledge”. IEEE Transactions on Industrial Informatics, no. 17, pp. 1039–1047, 2021.
dc.relation.references[11]O. Androshchuk, R. Berezenskyi, O. Lemeshko, A. Melnyk, and O. Huhul, “Model of Explicit Knowledge Management in Organizational and Technical Systems”, International Journal of Computing, vol. 20, no. 2, pp. 228-236, 2021. https://doi.org/10.47839/ijc.20.2.2170.
dc.relation.references[12]A. Melnyk and R. Pasichnyk, “System of semantic classes for test’s generation”, in Proc. International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET), pp. 206–206, 2010.
dc.relation.references[13]Lu, Jinzhi, Junda Ma, Xiaochen Zheng, Guoxin Wang and D. Kiritsis. “Design Ontology Supporting Model-based Systems-Engineering Formalisms”. ArXiv abs / 2010.07627 (2020): n. pag.
dc.relation.references[14]Ebrahimipour, V. and S. Yacout, “Ontology-Based Knowledge Platform to Support Health Equipment in Plant Operations”, 2015.
dc.relation.references[15]Abdelhadi Belfadel, Emna Amdouni, Jannik Laval, Chantal Cherifi, and Néjib Moalla, “Ontology-based Software Capability Container for RESTful APIs”, in Proc. 9th IEEE International Conference on Intelligent Systems (IS 2018), Sep 2018, Madeira, Portugal. ffhal-01877278.
dc.relation.references[16]Martina Husáková, and Vladimír Bureš, “Formal Ontologies in Information Systems Development: A Systematic Review”, Information 11, no. 2, p. 66. 2020. https://doi.org/10.3390/info11020066.
dc.relation.referencesen[1] M. Dyvak, N. Porplytsya, and Y. Maslyiak, "Modified Method of Structural Identification of Interval Discrete Models of Atmospheric Pollution by Harmful Emissions from Motor Vehicles", in Proc. Advances in Intelligent Systems and Computing IV. CSIT 2019, vol. 1080. Springer, Cham. 2020. https://doi.org/ 10.1007/978-3-030-33695-0_33.
dc.relation.referencesen[2] M. Dyvak, N. Porplytsya; and I. Borivets, and M. Shynkaryk, "Improving the computational implementation of the parametric identification method for interval discrete dynamic models". in Proc. 12th International Scientific and Technical Conference on Computer Science and Information Technologies (CSIT), Lviv, Ukraine, 5–8 September 2017; pp. 533–536, DOI: 10.1109, STCCSIT.2017.809884
dc.relation.referencesen[3] M. Dyvak, Y. Maslyiak and A. Pukas, "Information Technology for Modeling of Atmosphere Pollution Processes by Motor Vehicle Harmful Emissions", in Proc. IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), pp. 1–5, 2019. DOI: 10.1109, CADSM.2019.8779268.
dc.relation.referencesen[4] Mykola Dyvak, Parameters Identification Method of Interval Discrete Dynamic Models of Air Pollution Based on Artificial Bee Colony Algorithm, 2020, 130–135. 10.1109/ACIT49673.2020.9208972
dc.relation.referencesen[5] N. Ocheretnyuk, I. Voytyuk, M. Dyvak, and Ye. Martsenyuk, "Features of structure identification the macromodels for nonsta-tionary fields of air pollution from vehicles". in Proc. Modern Problems of Radio Engineering, Telecommunications and Computer Science, Proceedings of the 11th International Conference, Lviv, Ukraine, p. 444, 17–19 May, 2012.
dc.relation.referencesen[6] M. Dyvak, Y. Maslyiak and A. Pukas, "Information Technology for Modeling of Atmosphere Pollution Processes by Motor Vehicle Harmful Emissions", in Proc. IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), pp. 1–5, 2019. DOI: 10.1109, CADSM.2019.8779268.
dc.relation.referencesen[7] Munira Mohd Ali, Ruoyu Yang, Binbin Zhang, Francesco Furini, Rahul Rai, J. Neil Otte, and Barry Smith, "Enriching the functionally graded materials (FGM) ontology for digital manufacturing", International Journal of Production Research 0: 0, pp. 1–18, 2020.
dc.relation.referencesen[8] Suresh, P., G. Joglekar, Shuo-Huan Hsu, P. Akkisetty, Leaelaf Hailemariam, Ankur Jain, G. Reklaitis and V. Venkatasubramanian. "Onto MODEL: Ontological mathematical modeling knowledge management". Computer-aided chemical engineering, no. 25, pp. 985–990, 2008.
dc.relation.referencesen[9] Trokanas, Nikolaos and F. Cecelja. "Ontology evaluation for reuse in the domain of Process Systems Engineering". Comput. Chem. Eng. no. 85, pp. 177–187, 2016.
dc.relation.referencesen[10]Yang, Lan, K. Cormican and Ming Yu. "Ontology Learning for Systems Engineering Body of Knowledge". IEEE Transactions on Industrial Informatics, no. 17, pp. 1039–1047, 2021.
dc.relation.referencesen[11]O. Androshchuk, R. Berezenskyi, O. Lemeshko, A. Melnyk, and O. Huhul, "Model of Explicit Knowledge Management in Organizational and Technical Systems", International Journal of Computing, vol. 20, no. 2, pp. 228-236, 2021. https://doi.org/10.47839/ijc.20.2.2170.
dc.relation.referencesen[12]A. Melnyk and R. Pasichnyk, "System of semantic classes for test’s generation", in Proc. International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET), pp. 206–206, 2010.
dc.relation.referencesen[13]Lu, Jinzhi, Junda Ma, Xiaochen Zheng, Guoxin Wang and D. Kiritsis. "Design Ontology Supporting Model-based Systems-Engineering Formalisms". ArXiv abs, 2010.07627 (2020): n. pag.
dc.relation.referencesen[14]Ebrahimipour, V. and S. Yacout, "Ontology-Based Knowledge Platform to Support Health Equipment in Plant Operations", 2015.
dc.relation.referencesen[15]Abdelhadi Belfadel, Emna Amdouni, Jannik Laval, Chantal Cherifi, and Néjib Moalla, "Ontology-based Software Capability Container for RESTful APIs", in Proc. 9th IEEE International Conference on Intelligent Systems (IS 2018), Sep 2018, Madeira, Portugal. ffhal-01877278.
dc.relation.referencesen[16]Martina Husáková, and Vladimír Bureš, "Formal Ontologies in Information Systems Development: A Systematic Review", Information 11, no. 2, p. 66. 2020. https://doi.org/10.3390/info11020066.
dc.relation.urihttps://doi.org/
dc.relation.urihttps://doi.org/10.47839/ijc.20.2.2170
dc.relation.urihttps://doi.org/10.3390/info11020066
dc.rights.holder© Національний університет „Львівська політехніка“, 2022
dc.subjectmathematical modeling
dc.subjectinterval analysis
dc.subjectknowledge management
dc.subjectontological approach
dc.titleControl of Mathematical Modeling Process of Dynamics of Harmful Substances Concentrations on the Basis of Ontological Approach
dc.title.alternativeУправління процесом математичного моделювання динаміки концентрацій шкідливих речовин на основі онтологічного підходу
dc.typeArticle

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Computational Problems Of Electrical Engineering. – 2022. – Vol. 12, No. 1