National projects and government programmes
Functional algorithm for evaluating and modelling using the Data Science methodology
Bibliographic Data
| ID | 21780260 |
|---|---|
| Authors | Олим Астанакулов (0000-0002-0536-1214, corresponding author) |
| Year | 2020 |
| Volume | 183 |
| Issue | 5-6 |
| Pages | 51-59 |
| Publication date | 2020-06-04 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Economic Annals-ХХI (JOURNAL) |
| Journal identifiers | ISSN: 1728-6220 • E-ISSN: 1728-6239 |
| Publisher | Institute of Society Transformation sp. z o.o. (PUBLISHER) |
| DOI | 10.21003/ea.v183-05 |
| OpenAlex | W3119704717 |
| Language | EN |
| Citations received | 1 |
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
Algorithm · Artificial neural network · Fuzzy logic · Legislature · Machine learning · Management science · Operations research · Political science · Process management · Computer Science · Digitalization and Economic Development in Agriculture · Economic and Technological Developments in Russia · Economic and Technological Systems Analysis · Engineering · Artificial Intelligence
| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |