https://oldena.lpnu.ua/handle/ntb/52476| Title: | Intelligent Analysis of Data Systems for Defects in Underground Gas Pipeline |
| Authors: | Yuzevych, Volodymyr Skrynkovskyy, Ruslan Koman, Bohdan |
| Affiliation: | Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine Lviv University of Business and Law Ivan Franko National University of Lviv |
| Bibliographic description (Ukraine): | Yuzevych V. Intelligent Analysis of Data Systems for Defects in Underground Gas Pipeline / Volodymyr Yuzevych, Ruslan Skrynkovskyy, Bohdan Koman // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 134–138. — (Dynamic Data Mining & Data Stream Mining). |
| Bibliographic description (International): | Yuzevych V. Intelligent Analysis of Data Systems for Defects in Underground Gas Pipeline / Volodymyr Yuzevych, Ruslan Skrynkovskyy, Bohdan Koman // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 134–138. — (Dynamic Data Mining & Data Stream Mining). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | data mining gas pipeline intelligent software hardware monitoring cathodic protection databases |
| Number of pages: | 5 |
| Page range: | 134-138 |
| Start page: | 134 |
| End page: | 138 |
| Abstract: | A method of functioning of intelligent software and hardware complex for monitoring system of an underground gas pipeline and cathodic protection devices using data and knowledge bases is proposed. |
| URI: | https://ena.lpnu.ua/handle/ntb/52476 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://doi.org/10.18287/2223-9537-2017-7-1-48-65 https://doi.org/10.21003/ea.v160-08 https://doi.org/10.1109/dsmp.2016.7583505 https://doi.org/10.1007/s11003-017-0016-8 https://doi.org/10.1002/j.1538-7305.1948.tb00917.x http://www.jatit.org/volumes/Vol47No3/61Vol47No3.pdf https://doi.org/10.15407/mfint.39.12.1655 https://www.springer.com/us/book/9783540673699 |
| References (Ukraine): | [1] A. Cosham, and P. Hopkins, “An Overview of the pipeline defect assessment manual (PDAM),” proceedings of 4th International Pipeline Technology Conference, Oostende, Belgium, pp. 1-12, May 2004. [2] N. G. Gubanov, S. V. Susarev, Yu. I. Steblev, and V. I. Batishchev, “The method of functioning of an intelligent software and hardware complex for monitoring and ensuring the safety of pipeline operation using a database,” Proceedings of the XIX International Conference “Complex Systems: Control and Modeling Problems”, Samara, Russia, pp. 96-102, September 2017. [3] O. V. Barmina, and N. O. Nikulina, “Intelligent system for interactive business processes management in project-oriented organizations,” Ontology of designing. vol. 7, no. 1 (23), pp. 48-65, 2017. doi: https://doi.org/10.18287/2223-9537-2017-7-1-48-65 . [4] V. Yuzevych, O. Klyuvak, and R. Skrynkovskyy, “Diagnostics of the system of interaction between the government and business in terms of public e-procurement,” Economic Annals-ХХI, vol. 160, no. 7–8, pp. 39–44, Oct. 2016. doi: https://doi.org/10.21003/ea.v160-08 . [5] N. O. Komleva, K. S. Cherneha, B. I. Tymchenko, and O. M. Komlevoy, “Intellectual approach application for pulmonary diagnosis,” 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), Aug. 2016. doi: https://doi.org/10.1109/dsmp.2016.7583505 . [6] R. М. Dzhala, B. Y. Verbenets’, М. І. Mel’nyk, А. B. Mytsyk, R. S. Savula, and О. М. Semenyuk, “New Methods for the Corrosion Monitoring of Underground Pipelines According to the Measurements of Currents and Potentials,” Materials Science, vol. 52, no. 5, pp. 732–741, Mar. 2017. doi: https://doi.org/10.1007/s11003-017-0016-8. [7] R. Dzhala, V. Yuzevych, and М. Melnyk, “Modeling the adsorption connections and their influence on informational parameters of metalelectrolyte interface,” Bulletin of the Lviv Polytechnic National University, Series “Computer Sciences and Information Technologies”, no. 826, pp. 185–190, 2015. [8] C. E. Shannon, “A Mathematical Theory of Communication,” Bell System Technical Journal, vol. 27, no. 4, pp. 623–656, Oct. 1948. doi: https://doi.org/10.1002/j.1538-7305.1948.tb00917.x . [9] V. А. Sokolov, “Diagnostic weight of signs and diagnostic value of examination in recognition of the states of elements of building system,” Engineering and Construction Journal, no. 3(13), pp. 27-31, 2010. [10] N. A. Matveeva, L. Y. Martynovych, and U. V. Lazorenko, “Choice of the optimal neural network for determining defects in composite materials,” Bulletin of the Kherson National Technical University, no. 3(50), pp. 66-70, 2014. [11] P. Sibi, S. Allwyn Jones, and P. Siddarth, “Analysis of Different Activation Functions Using Back Propagation Neural Networks,” Journal of Theoretical and Applied Information Technology, vol. 47, no. 3, pp. 1264-1268, 2013. http://www.jatit.org/volumes/Vol47No3/61Vol47No3.pdf . [12] N. Krap, V. Yuzevych, “Neural Networks as a tool for managing the configurations of tourist flow projects,“ Management of Development of Complex Systems, no. 14, pp. 37-40, 2013. [13] I. Gulina, А. Martynenko, А. Gulin, “Construction of intelligent predictive control systems for nonlinear technological processes,” Information Processing Systems, no. 3 (149), pp. 101-105, 2017. [14] V. M. Yuzevych, R. M. Dzhala, and B. P. Koman, “Analysis of Metal Corrosion under Conditions of Mechanical Impacts and Aggressive Environments,” Metallofizika i Noveishie Tekhnologii, vol. 39, no. 12, pp. 1655–1667, Mar. 2018. doi: https://doi.org/10.15407/mfint.39.12.1655 . [15] G. E. P. Box, G. M. Jenkins, Time series analysis: forecasting and control. San Francisco, CA: Holden-Day. 1976. [16] O. Nelles, Nonlinear System Identification: From Classical Approaches to Neural and Fuzzy Models. Berlin: Springer, 2001. https://www.springer.com/us/book/9783540673699 . [17] J. H. Holland, Adaptation in natural and artificial systems. An introductory analysis with application to biology, control and artificial intelligence, London: Bradford book edition, 1994. |
| References (International): | [1] A. Cosham, and P. Hopkins, "An Overview of the pipeline defect assessment manual (PDAM)," proceedings of 4th International Pipeline Technology Conference, Oostende, Belgium, pp. 1-12, May 2004. [2] N. G. Gubanov, S. V. Susarev, Yu. I. Steblev, and V. I. Batishchev, "The method of functioning of an intelligent software and hardware complex for monitoring and ensuring the safety of pipeline operation using a database," Proceedings of the XIX International Conference "Complex Systems: Control and Modeling Problems", Samara, Russia, pp. 96-102, September 2017. [3] O. V. Barmina, and N. O. Nikulina, "Intelligent system for interactive business processes management in project-oriented organizations," Ontology of designing. vol. 7, no. 1 (23), pp. 48-65, 2017. doi: https://doi.org/10.18287/2223-9537-2017-7-1-48-65 . [4] V. Yuzevych, O. Klyuvak, and R. Skrynkovskyy, "Diagnostics of the system of interaction between the government and business in terms of public e-procurement," Economic Annals-KhKhI, vol. 160, no. 7–8, pp. 39–44, Oct. 2016. doi: https://doi.org/10.21003/ea.v160-08 . [5] N. O. Komleva, K. S. Cherneha, B. I. Tymchenko, and O. M. Komlevoy, "Intellectual approach application for pulmonary diagnosis," 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), Aug. 2016. doi: https://doi.org/10.1109/dsmp.2016.7583505 . [6] R. M. Dzhala, B. Y. Verbenets, M. I. Melnyk, A. B. Mytsyk, R. S. Savula, and O. M. Semenyuk, "New Methods for the Corrosion Monitoring of Underground Pipelines According to the Measurements of Currents and Potentials," Materials Science, vol. 52, no. 5, pp. 732–741, Mar. 2017. doi: https://doi.org/10.1007/s11003-017-0016-8. [7] R. Dzhala, V. Yuzevych, and M. Melnyk, "Modeling the adsorption connections and their influence on informational parameters of metalelectrolyte interface," Bulletin of the Lviv Polytechnic National University, Series "Computer Sciences and Information Technologies", no. 826, pp. 185–190, 2015. [8] C. E. Shannon, "A Mathematical Theory of Communication," Bell System Technical Journal, vol. 27, no. 4, pp. 623–656, Oct. 1948. doi: https://doi.org/10.1002/j.1538-7305.1948.tb00917.x . [9] V. A. Sokolov, "Diagnostic weight of signs and diagnostic value of examination in recognition of the states of elements of building system," Engineering and Construction Journal, no. 3(13), pp. 27-31, 2010. [10] N. A. Matveeva, L. Y. Martynovych, and U. V. Lazorenko, "Choice of the optimal neural network for determining defects in composite materials," Bulletin of the Kherson National Technical University, no. 3(50), pp. 66-70, 2014. [11] P. Sibi, S. Allwyn Jones, and P. Siddarth, "Analysis of Different Activation Functions Using Back Propagation Neural Networks," Journal of Theoretical and Applied Information Technology, vol. 47, no. 3, pp. 1264-1268, 2013. http://www.jatit.org/volumes/Vol47No3/61Vol47No3.pdf . [12] N. Krap, V. Yuzevych, "Neural Networks as a tool for managing the configurations of tourist flow projects," Management of Development of Complex Systems, no. 14, pp. 37-40, 2013. [13] I. Gulina, A. Martynenko, A. Gulin, "Construction of intelligent predictive control systems for nonlinear technological processes," Information Processing Systems, no. 3 (149), pp. 101-105, 2017. [14] V. M. Yuzevych, R. M. Dzhala, and B. P. Koman, "Analysis of Metal Corrosion under Conditions of Mechanical Impacts and Aggressive Environments," Metallofizika i Noveishie Tekhnologii, vol. 39, no. 12, pp. 1655–1667, Mar. 2018. doi: https://doi.org/10.15407/mfint.39.12.1655 . [15] G. E. P. Box, G. M. Jenkins, Time series analysis: forecasting and control. San Francisco, CA: Holden-Day. 1976. [16] O. Nelles, Nonlinear System Identification: From Classical Approaches to Neural and Fuzzy Models. Berlin: Springer, 2001. https://www.springer.com/us/book/9783540673699 . [17] J. H. Holland, Adaptation in natural and artificial systems. An introductory analysis with application to biology, control and artificial intelligence, London: Bradford book edition, 1994. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
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| 2018_Yuzevych_V-Intelligent_Analysis_of_134-138.pdf | 305.21 kB | Adobe PDF | View/Open | |
| 2018_Yuzevych_V-Intelligent_Analysis_of_134-138__COVER.png | 530.31 kB | image/png | View/Open |
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