Метод формирования критериальных оценок морфологических признаков технических систем
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Method for formation of criterial assessments of morphological signs of technical systems

idKorobkin D.M.

UDC 004.89
DOI: 10.26102/2310-6018/2020.31.4.021

  • Abstract
  • List of references
  • About authors

The purpose of the study is to develop a method for the formation of criterion assessments of morphological features of technical systems based on the analysis of trends identified in the patent array. One of the common ways to generate new technical solutions or improve the functional structure of a technical system is the procedure of morphological synthesis. To evaluate a new synthesized technical solution, an urgent approach is the use of criterion assessments of its constituent morphological features (technical functions of system elements). As a result of the application of methods for extracting technical functions in the DGH format ("Action" - "Object" - "Restriction") from Russian-language patents and in the SAO format ("Subject" - "Action" - "Object"), a term document is formed from English-language patents. the matrix. The content of the term-document matrix is modernized on the basis of the developed algorithm for comparing technical functions, using statistical analysis of the patent array using Word2Vec technology (identifying contextual synonyms). A method for the formation of criterion estimates of technical functions based on patent trends identified by clustering a patent array based on a term document matrix has been developed. A method for determining the criteria-based assessment of the significance of a technical function in the future time period by means of forecasting time series based on the ARIMA method has been formed.

1. Korobkin D.M., Fomenkov S.A., Kolesnikov S.A Metod sinteza funktsional'noy strukturyi novyih tehnicheskih resheniy na osnove dannyih patentnyih massivov. Modelirovanie, optimizatsiya i informatsionnyie tehnologii. 2019;7(2):135-148

2. Korobkin D.M., Fomenkov S.A., Kolesnikov S.G. Metod verifikatsii sintezirovannoy funktsional'noy strukturyi posredstvom postroeniya fizicheskogo printsipa deystviya tehnicheskoy sistemyi. Modelirovanie, optimizatsiya i informatsionnyie tehnologii. 2019;7(2):97-109.

3. Shabanov D.V., Korobkin D.M., Fomenkov S.A., Kolesnikov S.G. Formirovanie matritsyi "fizicheskie effektyi - tehnicheskie funktsii" na osnove dannyih analiza patentnyih massivov. Matematicheskie metodyi v tehnike i tehnologiyah - MMTT. 2019;7:94-99.

4. Korobkin D., Fomenkov S., Kolesnikov S., Lobeyko V., Golovanchikov A. Modification of physical effect model for the synthesis of the physical operation principles of technical system. Communications in Computer and Information Science (sm. v knigah). 2015;535:367-377.

5. Korobkin D.M., Fomenkov S.A., Kolesnikov S.G., Golovanchikov A.B. Technical function discovery in patent databases for generating innovative solutions. V sbornike: Proceedings of the International Conferences on ICT, Society, and Human Beings 2016, Web Based Communities and Social Media 2016, Big Data Analytics, Data Mining and Computational Intelligence 2016 and Theory and Practice in Modern Computing 2016 - Part of the Multi Conference on Computer Science and Information Systems 2016. 2016:241-245

6. Korobkin D.M., Vasiliev S.S., Fomenkov S.A., Lobeyko V.I. Extraction of structural elements of inventions from russian-language patents. V sbornike: Multi Conference on Computer Science and Information Systems, MCCSIS 2019 - Proceedings of the International Conferences on Big Data Analytics, Data Mining and Computational Intelligence 2019 and Theory and Practice in Modern Computing 2019. 4. 2019:159-166.

7. Kharitonov A., Korobkin D., Fomenkov S., Kolesnikov S. Extraction of morphological features of technical systems from russian patent. V sbornike: CEUR Workshop Proceedings. IS 2019 - Proceedings of the 14th International Conference on Interactive Systems: Problems of Human-Computer Interaction. 2019:205-213

8. Serge, Sonfack. Word2Vec how it works. 2019. DOI: 10.13140/RG.2.2.12524.51844.

9. Zhang, Meng & Li, Wei & Zhang, Bo. A Novel Method to Solve the Separation Problem of LDA. 2020. DOI: 10.1007/978-3-030-46931-3_6.

10. Sanjoyo, Sanjoyo. ARMA ARIMA ARCA GARCH. 2020. DOI: 10.13140/RG.2.2.29139.81445.

Korobkin Dmitriy Michaylovich
PhD in Engineering Science, Associate Professor

ORCID |

Volgograd State Technical University

Volgograd, Russian Federation

Keywords: morphological analysis, dGH, sAO, patents, fact extraction, trend, aRIMA

For citation: Korobkin D.M. Method for formation of criterial assessments of morphological signs of technical systems. Modeling, Optimization and Information Technology. 2020;8(4). URL: https://moitvivt.ru/ru/journal/pdf?id=867 DOI: 10.26102/2310-6018/2020.31.4.021 (In Russ).

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Published 31.12.2020