Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 377 - 388
Опубликована: Янв. 1, 2024
Язык: Английский
Qubahan Academic Journal, Год журнала: 2025, Номер 4(4), С. 306 - 317
Опубликована: Янв. 1, 2025
The development of the tourism sector faces serious challenges, which are related to its environmental transformation, digitalization, and integration new technologies, as well competitiveness. Tourists' behavior is also changing. future demand for likely be driven by growing awareness, increased use digital services a shift towards more personalized travel experience, ensuring well-being better engagement with local communities culture. Meeting requirements modern industry problem not only Republic Kazakhstan but other countries that strive sustainable sector. purpose study identify ways develop entrepreneurial activity integrating human capital green technologies optimize paper examines basic theoretical concepts essence forms presents concept achieve principles development. Based on an expert survey, strengths, weaknesses, opportunities, threats analysis, statistical methods, main promotion tourism, measures integrate into activities in East Region, have been identified. authors concluded introduction them provide standards quality tourist while preserving natural resources region.
Язык: Английский
Процитировано
0
Systems and Soft Computing, Год журнала: 2025, Номер 7, С. 200215 - 200215
Опубликована: Март 4, 2025
Язык: Английский
Процитировано
0
Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown
Опубликована: Март 26, 2025
Язык: Английский
Процитировано
0
BIO Web of Conferences, Год журнала: 2024, Номер 140, С. 06007 - 06007
Опубликована: Янв. 1, 2024
This research paper addresses the critical need for an advanced framework to elevate financial analysis of cluster activities. Clusters, defined as geographically proximate groups interconnected companies and associated institutions in a particular field, have emerged key drivers economic growth. However, existing methods often fall short capturing complex dynamics interdependencies within these clusters. The delves into current challenges limitations conventional context It highlights inadequacy standard metrics unique characteristics synergies inherent clusters, leading suboptimal decision-making processes. By integrating data analytics, risk assessment models, qualitative assessments, aims provide holistic view landscape Also explores broader impact on regional development potential scalability across various industries. contributes ongoing discourse methodologies, specifically tailored proposed offers sophisticated practical solution address shortcomings approaches, thereby empowering stakeholders make more informed decisions dynamic cluster- based economies.
Язык: Английский
Процитировано
0
BIO Web of Conferences, Год журнала: 2024, Номер 140, С. 03015 - 03015
Опубликована: Янв. 1, 2024
The research objective is to identify the most promising areas of digitalization in field food security Russia. methodological basis study comparative analysis. It was used determine consequences use digital technologies various based on 2021 statistical data. Results. author defined Russian model for ensuring Russia, revealing agriculture Russia: financial settlements electronic form, access databases via Internet, and document management systems. prospects are related specification economic returns from each seen viewpoint quantitative measurement. empirical value revealed improving sphere explained by fact that orientation state regulators economy towards it will ensure maximum potential strengthening Russia 2030-2031.
Язык: Английский
Процитировано
0
Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 203 - 218
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0
AIMS Mathematics, Год журнала: 2024, Номер 9(11), С. 33314 - 33352
Опубликована: Янв. 1, 2024
<p>Investment risk forecasting is challenging when the stock market characterized by non-linearity and extremes. Under these conditions, VaR estimation based on assumption of distribution normality becomes less accurate. Combining extreme value theory (EVT) with machine learning (ML) produces a model that detects learns heavy tail patterns in data distributions containing values while being effective non-linear systems. We aimed to develop an investment capital characteristics using method EVT approach combined ML (VaR<sub>GPD-ML(α)</sub>). The combination methods used multivariate time series RNN, LSTM, GRU algorithms obtain ML-based returns. POT was for estimation. backtesting validate model. Our results showed determining threshold normal will identify ideal number, minimum bias, following GPD. VaR<sub>GPD-ML(α)</sub> valid all samples at α = 0.95 0.99. Generally, this greater estimated than VaR<sub>GPD(α)</sub> 95% confidence level.</p>
Язык: Английский
Процитировано
0
Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 377 - 388
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0