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

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.

Enhancing Housing Finance for Socio-Economic Stability in Uzbekistan

“…The volume of investments in housing construction in Uzbekistan in 2023 reached 54.7 trillion soums ($5.1 billion), which is 2.8 times higher than the figure for 2018-19.6 trillion soums ($2.3 billion) (Figure 1). The share of investments in housing construction in the total volume of investments in fixed capital increased from 9.4% in 2018 to 12.1% in 2023 (Astanakulov et al, 2020). The main sources of financing for housing construction are the funds of the population (52.3% in 2023), loans from commercial banks (24.8%), budgetary funds (12.5%), and funds of enterprises and organizations (10.4%) (Jia, 2021).…”

“…These formulas provide a mathematical representation of some of the key findings of the study and can be used to analyze the dynamics and interrelationships between various factors influencing the development of housing finance in Uzbekistan (Abduvaliev, et al, 2023;Saali et al, 2024). However, it is important to note that these formulas are based on the specific data and assumptions used in the study and may need to be adjusted or expanded to account for additional variables and changing market conditions (Astanakulov, 2020).…”

Tourism as a catalyst for regional development: Uzbekistan’s experience and economic prospects

“…The academic investigation into the role of tourism as a catalyst for regional development, particularly in the context of Uzbekistan, comprises a rich tapestry of multi-disciplinary perspectives (Parshukov, 2021). The emergent narrative coalesces around several pivotal domains that include but are not limited to economic implications, socio-cultural dynamics, policy intervention strategies, and sustainability paradigms (Astanakulov, 2020).…”

Ciencia de datos en la evaluación del impacto de las políticas públicas: Una revisión de la literatura

“…¿Qué niveles de soporte tendrían los humanos si las decisiones tomadas por la IA son cuestionables? Por otro lado, respecto a la incertidumbre, Knüsel et al (2020) recomiendan realizar una mayor investigación sobre los principios que deben tenerse en cuenta para la toma de decisiones en situación de incertidumbre, así como en métodos para la cuantificación de la incertidumbre de segundo orden; en esta misma línea, Astanakulov (2020) también señala que las incertidumbres se consideran factores que afectan negativamente al proceso de modelización, conducen a diversos errores y reducen la calidad de los resultados finales, por lo que estas deben ser investigadas sobre todo con enfoques cuantitativos.…”