Intellectual support for the analysis of the implementation of innovative development programs of the regional agro-industrial cluster

Lomazov, V A; Ломазов, Александр Вадимович; Ivashchuk, Olga A.; Akupiyan, Olga; Нестерова, Е. В.

doi:10.1088/1755-1315/839/2/022068

Cited by 7 publications

(5 citation statements)

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“…The proposed approach to assessing the dependability of biogas energy systems is based on the use of a constructed hierarchy of indicators and the application of methods from the theory of artificial intelligence (neural networks, representation of knowledge in the form of fuzzy production rules). The constructed procedure for determining dependability indicators (from primary statistical indicators to an integral indicator) allows us to formalize the analysis process and can be used as part of decision support (in accordance with [21]) when choosing design solutions and subsequent operation of biogas energy, taking into account local (regional) specifics.…”

Section: Discussionmentioning

confidence: 99%

Multicriteria fuzzy statistical analysis of biogas energy systems dependability

Lomazov,

Klyosov

et al. 2024

E3S Web of Conf.

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The work is devoted to the problems of assessing the dependability of autonomous energy systems with biogas type of electrical generation. The purpose of the work is to develop an intelligent tool for multi-criteria dependability assessment, taking into account the statistical uncertainty of individual indicators. A three-level hierarchy (according to the degree of generalization) of dependability indicators, represented by statistical (at the lower level) and fuzzy linguistic (starting from the second level) variables, has been developed. It is proposed to implement the transition from statistical values of lower-level indicators to numerical values of second-level indicators using an artificial neural network. Fuzzification of second-level indicators was carried out using L. Zadeh’s z-number apparatus, which allows taking into account statistical uncertainty. To determine the integral dependability indicator (top of the hierarchy) based on second-level indicators, it is proposed to use the Mamdani fuzzy inference algorithm. The constructed procedure for determining the level of dependability allows us to obtain data for making scientifically based decisions when operating biogas energy systems.

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Section: Discussionmentioning

confidence: 99%

Multicriteria fuzzy statistical analysis of biogas energy systems dependability

Lomazov,

Klyosov

et al. 2024

E3S Web of Conf.

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“…In relations (5), the values of the considered intermediate indicator InterIndi are assumed to be measured during TimeTermon the territory of TerTerm* under external conditions ExIndTerm*,, which corresponds to the fulfillment (with some degree of truth) of the statements: Time -TimeTerm*, Ter -TerTerm*, ExInd -ExIndTerm* (TimeTerm*TStage, TerTerm*TTer, ExIndTerm*TInd). If the left part of the fuzzy production rule ( 5) is satisfied (with some degree of truth), then its right part is satisfied (with some degree of truth), which is a fuzzy statement TargIndp -TargIndTermk regarding the target indicator TargIndp, which consists in the fact that this indicator accepts a linguistic value (term) TargIndTermk.…”

Section: Indicative-temporal-territorial Production Dependenciesmentioning

confidence: 99%

“…Relations (5) (in contrast to relations (2) having the structure IF-TIEN-) having the structure IF-WHEN-WHERE-WHITTH-TIEN-will be called W-rules. We will assume that W-rules (as well as fuzzy rules (2)) are set by experts based on their knowledge of the subject area of the project.…”

Section: Indicative-temporal-territorial Production Dependenciesmentioning

confidence: 99%

“…private-state projects (in particular, in relation to projects of sustainable development of rural areas [1][2][3]). In modern conditions, which are characterized by a high level of instability and unpredictability of project implementation conditions, the ability to predict results when external conditions change [4], which is especially important for long-term multi-stage projects of an innovative nature, is of greater importance [5]. Forecasting the final results allows you to make timely adjustments to the project activities, implementing adaptive management [6,7].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy linguistic forecasting of the results of the implementation of regional socio-economic projects

Lomazov,

Akupian

et al. 2023

E3S Web Conf.

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The article is devoted to the problem of improving the intellectual digital support for managing the implementation of regional socio-economic projects, which are an effective mechanism for the development of regions. Given the high level of uncertainty in the description of the subject area, it is proposed to use expert technologies to assess the degree of achievement of the intermediate and target indicators of the project. L. Zadeh's linguistic modeling apparatus was used as the basis for intellectual tools for representing and processing expert judgments. A linguistic indicative-temporal-territorial model of the project has been built in the form of a set of linguistic variables and a system of fuzzy production rules linking these variables. At the same time, temporal and territorial linguistic variables reflect the time and place of measurement of project indicators, the incomplete correspondence of which determines the degree of reliability of the measured values of indicators. The use of the constructed system of indicative-temporal-territorial fuzzy production rules makes it possible to link the intermediate values of the indicators with the target values of the project indicators and thereby predict the possible outcomes of its implementation. For this, a fuzzy logic inference procedure based on the use of the Mamdani algorithm has been developed. Preliminary results of using a research prototype of an intelligent expert system for analyzing the intermediate results of the project stages and predicting its results may indicate the effectiveness of the proposed approach.

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“…The currently existing methodological apparatus of the theory of project management does not fully allow taking into account the specifics of regional eco-projects, which consists not only in the delay in the manifestation of the effects of the implementation of activities and the limited resources of regional authorities, but also in the widespread involvement of public organizations in the planning and implementation of projects [9,10]. In methodological terms, this gives rise to the need to take into account the high level of uncertainty inherent in regional environmental projects [11,12].The purpose of this study is to develop a methodological apparatus for adaptive management of multi-stage regional ecoprojects based on knowledge about the patterns of the subject area of the project, represented by a system of linguistic variables and fuzzy production rules connecting them.…”

Section: Introductionmentioning

confidence: 99%

Decision support in the management of multi-stage regional environmental projects

Lomazov

Akupiyan

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

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The article deals with the problem of multi-criteria assessment and management of the implementation of multi-scenario multi-stage regional environmental projects. The proposed approach involves building a scenario network, each node of which corresponds to a set of activities of a certain stage. The choice of the arc of transition to the next stage (the option of continuing the project) is made on the basis of knowledge about the subject area of the project, represented by a system of linguistic variables and fuzzy production rules linking them. The recommended solution for choosing the continuation of the project is determined based on the fuzzy inference procedure. The final choice of the option to continue the implementation of the environmental project is made by the decision-maker on the basis of their own (often non-formalized) preferences. As an example of the application of the proposed approach, the task of managing regional forest conservation projects is considered. The use of the developed decision support tools for adaptive management of environmental projects makes it possible to increase the scientific validity of management decisions, and, consequently, to reduce costs and increase environmental efficiency in the implementation of these projects.

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Intellectual support for the analysis of the implementation of innovative development programs of the regional agro-industrial cluster

Cited by 7 publications

References 1 publication

Multicriteria fuzzy statistical analysis of biogas energy systems dependability

Multicriteria fuzzy statistical analysis of biogas energy systems dependability

Fuzzy linguistic forecasting of the results of the implementation of regional socio-economic projects

Decision support in the management of multi-stage regional environmental projects

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