Fuzzy Modelling in Risk Assessment of Oil and Gas Production Enterprises’ Activity

Fadyeyeva, Iryna; Gryniuk, Oksana

doi:10.30525/2256-0742/2017-3-4-256-264

Cited by 4 publications

(6 citation statements)

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“…Centralized databases were historically the first databases in enterprises. The database theory was formulated in [Coronel and Morris 2017;Elmasri and Navathe 2017]. A database is a standard tool for structuring management processes in larger organizations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Because of that they choose systems which ensure that decisions are made at local branches, but at the same time enable the transfer of information as comprehensive as possible from/to the headquarters in order to maximize the synergy effect. A fuzzy database system is a natural choice in such situations [Elmasri and Navathe 2017]. For the reasons set above, making the information accessible to the users from the outside of the organization is a major challenge for information management within a company.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The concept of data warehouse (DW) -a structure enabling decision makers to make optimal decisions on the basis of various sources -was established as an answer to the needs of large corporations requiring a solution for processing data for business purposes [Elmasri and Navathe 2017]. In fact, data warehouses are databases integrating data from all the other database systems within the enterprise.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The article describes identifying "missing" and "hidden" data during processing well-defined quires to the database. Additionally, it explains the importance of this issue and discusses the problem of organizing, processing and implementing fuzzy queries into database information systems [Fadyeyeva and Gryniuk 2017]. Another article provides a complete marketing system of enterprise-orientated fuzzy queries.…”

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

From Classical to Fuzzy Databases in a Production Enterprise

Rojek¹,

Mikołajewski²,

Kotlarz³

et al. 2020

jucs

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This article presents the evolution of databases from classical relational databases to distributed databases and data warehouses to fuzzy databases used in a production enterprise. This paper discusses characteristics of this kind of enterprise. The authors precisely define centralized and distributed databases, data warehouses and fuzzy databases. In the modern global world, many companies change their management strategy from the one based on a centralized database to an approach based on distributed database systems. Growing expectations regarding business intelligence encourage companies to deploy data warehouses. New solutions are sought as the demand for engineers' expertise continues to rise. The requested knowledge can be certain or uncertain. Certain knowledge does not any problems and is easy to obtain. However, uncertain knowledge requires new ways of obtaining, including the use of fuzzy logic. It is from where the fuzzy database approach takes its beginning. The above-mentioned strategies of a production enterprise were described herein as a case of special interest.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

From Classical to Fuzzy Databases in a Production Enterprise

Rojek¹,

Mikołajewski²,

Kotlarz³

et al. 2020

jucs

View full text Add to dashboard Cite

show abstract

“…Based on the results of the analysis of pragmatic value of information regarding risk events at the business entities under investigation, we have identified six groups of risk forming factors, that have a negative impact, and design structure of the six-level risk assessment model of the operating activity of oil and gas companies based on Fuzzy Logic [13].…”

Section: The Seventh Information Situationmentioning

confidence: 99%

Fuzzy Approach to Risk-Controlling in Oil and Gas Company Management

Fadyeyeva¹,

Gryniuk²,

Mandryk³

et al. 2019

Proceedings of the 2019 7th International Conference on Modeling, Development and Strategic Management of Economic System (MDSM

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The article is devoted to the development and improvement of methodology and implementation of riskcontrolling subsystem in the management system of oil and gas companies in under uncertainty conditions. It is proved, that the mathematical tool of Fuzzy Logic allows to reveal and take into account complicated nonlinear dependences between quantitative and qualitative indicators of risk-event probability estimation, and also mutual effect of risk forming factors. The six-level system of evaluation of risks of operating activities of oil and gas companies, based on fuzzy logic has been established. It allows to take into account the non-linear nature of the relationship between the risk forming factors and the resulting indicator. The logical inference model has been designed. It shows the dependence of the risk level on the meaning of linguistic rules about groups of risk forming factors in different risk groups and which is the basis for the risk assessment model. The conceptual model of management of oil and gas companies with the risk-controlling subsystem as a part of it, the main element of which is the fuzzy model of risk assessment and forecasting, has been proposed. The research concluded, that the implementation of the proposed model of management of oil and gas production enterprises will significantly improve the efficiency of the upstream segment enterprises and significantly reduce losses, caused by the occurrence of risk-events.

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Анализ Рисков Информационной Безопасности В Пищевой Промышленности С Использованием Системы Нечеткого Вывода

Asfha,

Vaish

2023

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Recently, different attempts have been made to characterize information security threats, particularly in the industrial sector. Yet, there have been a number of mysterious threats that could jeopardize the safety of food processing industry data, information, and resources. This research paper aims to increase the efficiency of information security risk analysis in food processing industrial information systems, and the participants in this study were experts in executive management, regular staff, technical and asset operators, third-party consultancy companies, and risk management professionals from the food processing sector in Sub-Saharan Africa. A questionnaire and interview with a variety of questions using qualitative and quantitative risk analysis approaches were used to gather the risk identifications, and the fuzzy inference system method was also applied to analyze the risk factor in this paper. The findings revealed that among information security concerns, electronic data in a data theft threat has a high-risk outcome of 75.67%, and human resource management (HRM) in a social engineering threat has a low-risk impact of 26.67%. Thus, the high-probability risk factors need quick action, and the risk components with a high probability call for rapid corrective action. Finally, the root causes of such threats should be identified and controlled before experiencing detrimental effects. It's also important to note that primary interests and worldwide policies must be taken into consideration while examining information security in food processing industrial information systems.

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Fuzzy Modelling in Risk Assessment of Oil and Gas Production Enterprises’ Activity

Cited by 4 publications

References 0 publications

From Classical to Fuzzy Databases in a Production Enterprise

From Classical to Fuzzy Databases in a Production Enterprise

Fuzzy Approach to Risk-Controlling in Oil and Gas Company Management

Анализ Рисков Информационной Безопасности В Пищевой Промышленности С Использованием Системы Нечеткого Вывода

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