National projects and government programmes: Functional algorithm for evaluating and modelling using the Data Science methodology

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Abstract

Programme and target planning procedures in Russia have a lot of shortcomings, related to the selection of priority goals, establishment of criteria for evaluating the effectiveness of target programmes, as well as achievement of goals, development of a system of performance indicators, and so on. In addition, the problem of the lack of a high-quality theoretical and legislative framework for the transition to budget expenditures planning in accordance with the principles of result-oriented budgeting remains urgent. The purpose of this paper is to develop a functional fuzzy computing algorithm for modelling the evaluation of government programmes using neural networks. As a part of this work, we obtained stable results in the form of creating a neural network that can analyze government projects using a multi-criteria method, taking into account the root-mean-square error, with an accuracy of up to 95%. The analysis criteria cover all effective areas for predicting the correct use of the government projects by implementing them in the government systems.

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APA

Astanakulov, O. (2020). National projects and government programmes: Functional algorithm for evaluating and modelling using the Data Science methodology. Economic Annals-XXI, 183(5–6), 51–59. https://doi.org/10.21003/EA.V183-05

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