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Tytuł:
Identification of research areas in fuel sales forecasting within the business ecosystem context: A review, theoretical synthesis, and extension
Autorzy:
Zema, Tomasz
Sulich, Adam
Hernes, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/31234040.pdf
Data publikacji:
2024
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
fuel sales forecasting
business ecosystems
hybrid literature review
petroleum products
Opis:
Aim/purpose – This paper aims to explore both fuel sales forecasting and the business ecosystem, subsequently reversing the focus to examine the business ecosystem in the context of fuel sales forecasting. Accompanying this research objective are the following research questions: 1) Does the order in which the topics of “business ecosystems” and “fuel sales forecasting” are searched affect the search results? 2) Which keywords frequently co-occur in publications related to “business ecosystems” and “fuel sales forecasting”? 3) What is the relationship between the terms “fuel sales forecasting” and “business ecosystem”? Design/methodology/approach – The study employs a hybrid review methodology, utilizing specific queries within the Scopus database to identify research themes and motifs. This hybrid form of literature review integrates the tenets of both bibliometric and structured reviews. In this study, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was employed. The visual analysis was conducted using VOSviewer bibliometric software, with a focus on keywords relevant to the relationship between fuel sales forecasting and business ecosystem terms. Findings – Key findings include the identification of co-occurring keywords in fuel sales forecasting and business ecosystem theory literature. The study reveals research gaps and potential areas for future study in business ecosystems, highlighting the impact of fuel sales forecasting in various economic sectors beyond traditional ones, like forestry, agriculture, and fisheries. Utilizing a hybrid literature study research method, the paper analyses data from scientific publications in the Scopus database and employs VOSviewer software to develop bibliometric maps of keyword co-occurrences. Research implications/limitations – The research underscores the broad implications of fuel sales forecasting within a business ecosystem context and identifies areas lacking in-depth study. This study maps scientific publications, identifying the intellectual structure and current research trends. This study contributes to the understanding of fuel sales forecasting within the business ecosystem context as a part of the energy sector transition. Originality/value/contribution – This paper contributes to the field of science and practice by identifying research areas integrating fuel sales forecasting within the business ecosystem construct. It indicates future promising research avenues for researchers and industry professionals, aiming to guide ongoing research. The article addresses a significant theme that warrants scholarly attention. This study allows researchers to define the research gaps covered by published articles and indicate the directions of scientific development.
Źródło:
Journal of Economics and Management; 2024, 46; 79-110
1732-1948
Pojawia się w:
Journal of Economics and Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Aggregating sea surface hydrodynamic forecasts from multi-models for European seas
Autorzy:
Frishfelds, V.
She, J.
Murawski, J.
Nielsen, J. W.
Powiązania:
https://bibliotekanauki.pl/articles/24201473.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
weather research and forecasting
search and rescue
operational ocean forecasting
European Satellite Systems
surface current
drifting sea surface temperature
European waters
Opis:
Maritime information services supporting European agencies such as the FRONTEX require European‐wide forecast solutions. Following a consistent approach, regional and global forecasts of the sea surface conditions from Copernicus Marine Service and national met‐ocean services are aggregated in space and time to provide a European‐wide forecast service on a common grid for the assistance of Search and Rescue operations. The best regional oceanographic model solutions are selected in regional seas with seamless transition to the global products covering the Atlantic Ocean. The regional forecast models cover the Black Sea, Mediterranean Sea, Baltic Sea, North Sea and combine the North Sea – Baltic Sea at the Danish straits. Two global models have been added to cover the entire model domain, including the regional models. The aggregated product is required to have an update frequency of 4 times a day and a forecasting range of 7 days, which most of the regional models do not provide. Therefore, smooth transition in time, from the shorter timerange, regional forecast models to the global model with longer forecast range are applied. The set of parameter required for Search and Rescue operations include sea surface temperature and currents, waves and winds. The current version of the aggregation method was developed for surface temperature and surface currents but it will be extended to waves in latter stages. The method relies on the calculation of aggregation weights for individual models. For sea surface temperature (SST), near real‐time satellite data at clear‐sky locations for the past days is used to determine the aggregation weights of individual forecast models. A more complicated method is to use a weighted multi‐model ensemble (MME) approach based on best forecast features of individual models and possibly including near real time observations. The developed method explores how satellite observations can be used to assess spatially varying, near real time weights of different forecasts. The results showed that, although a MME based on multiple forecasts only may improve the forecast, if the forecasts are unbiased, it is essential to use observations in the MME approach so that proper weights from different models can be calculated and forecast bias can be corrected. It is also noted that, in some months, e.g., June in Baltic Sea, even SST was assimilated, the forecast still show quite high error. There are also visible difference between different Copernicus Marine Environment Monitoring Service (CMEMS) satellite products, e.g. OSTIA and regional SST products, which can lead different forecast quality if different SST observation products are assimilated.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 3; 533--541
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of exponential smoothing method to forecasting daily water consumption in rural areas
Zastosowanie metody wygładzania wykładniczego do prognozowania dobowego zużycia wody w obszarach wiejskich
Autorzy:
Cieżak, Wojciech
Kutyłowska, Małgorzata
Powiązania:
https://bibliotekanauki.pl/articles/27312154.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
prognozowanie
sieć przewodów
wygładzanie wykładnicze
zużycie wody
forecasting
exponential smoothing
pipe network
water consumption
Opis:
The size and distribution of water demand within a given structural unit is the basis for the proper operation and planning of the expansion and modernization of the water supply system’s elements. In rural areas, particularly in municipalities adjacent to urban-industrial agglomerations, a change in the use of tap water has been increasingly observed. The water consumption for animal breeding or agricultural use, typical of these areas, has been decreasing and even disappearing. Water has been increasingly used for domestic purposes in single- and multi-family housing as well as for other purposes such as watering lawns and filling residential swimming pools. Taking this into account, this paper presents observations regarding daily water consumption in a municipality adjacent to Wrocław together with an analysis of the possibility of using the exponential smoothing method for the short-term forecasting of daily water consumption. The analyses presented in this paper were carried out using STATISTICA 13 software.
Wzrost zapotrzebowania na wodę w gminach przyległych do dużych aglomeracji, a co za tym idzie wzrost produkcji wody, zmuszają przedsiębiorstwa wodociągowe do szukania nowych rozwiązań dotyczących między innymi optymalnego sterowania takimi procesami jak: ujmowanie i rozdział dyspozycyjnych zasobów wodnych, dystrybucja oraz oczyszczanie wody i ścieków. Aby zapewnić skuteczne sterowanie tymi procesami wymagany jest między innymi skalibrowany model hydrauliczny sieci dystrybucji i model prognostyczny poboru wody. Do bieżącego i krótkoterminowego prognozowania poboru wody wykorzystywane są modele stochastyczne, wprowadzane w postaci zalgorytmizowanej do struktury zarządzania procesem sterowania. Najczęściej stosowane są scałkowane modele autoregresji i średniej ruchomej ARIMA oraz metody wygładzania wykładniczego szeregów czasowych. Modele klasy ARIMA odwzorowują właściwości statyczne i dynamiczne szeregów stacjonarnych i pewnych klas szeregów niestacjonarnych, interpretowanych jako wynik przejścia białego szumu przez dyskretny filtr liniowy skończenie wymiarowy. Charakteryzują się one różnymi właściwościami przy jednolitym zapisie formalnym oraz identycznych metodach estymacji parametrów dla różnych typów i podklas modeli. Metody prognozowania oparte na algorytmach wygładzania wykładniczego są łatwe do praktycznego zastosowania i nie wymagają założenia o stacjonarności analizowanego szeregu czasowego. W niniejszej pracy przedstawiono obserwacje dotyczące dobowego zużycia wody w jednej z gmin przyległej do Wrocławia wraz z analizą możliwości zastosowania metody wygładzania wykładniczego do krótkoterminowego prognozowania dobowego poboru wody.
Źródło:
Archives of Civil Engineering; 2023, 69, 3; 445--456
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative analysis of methods for hourly electricity demand forecasting in the absence of data - a case study
Analiza porównawcza metod prognozowania godzinnego zapotrzebowania na energię elektryczną przy brakach w danych - studium przypadku
Autorzy:
Zawadzki, Jan
Powiązania:
https://bibliotekanauki.pl/articles/2194900.pdf
Data publikacji:
2023
Wydawca:
Akademia Bialska Nauk Stosowanych im. Jana Pawła II w Białej Podlaskiej
Tematy:
forecasting
missing data
time series
high frequency
Opis:
Scope and purpose of work: This paper examines the impact of the number of gaps in data, the analytical form, and the model type selection criterion on the accuracy of interpolation and extrapolation forecasts for hourly data. Materials and methods: Forecasts were developed on the basis of predictors that are based on: classical time series forecasting models and regression time series forecasting models, hybrid time series forecasting models and hybrid regression forecasting models for uncleared series, and exponential smoothing models for cleared series of two or three types of seasonal fluctuations, with minimum estimates of errors in interpolation or extrapolation forecasts. Results: Adaptive and hybrid regression models have proved to have the most favorable predictive properties. Most hybrid time series models for systematic and non-systematic gaps and for both analytical forms are single models that generally describe fluctuations within a 24-hour cycle. Conclusions: The lowest estimators of prediction errors involving interpolation were obtained for exponential smoothing models, followed by hybrid regression models. A reverse sequence was obtained for extrapolative forecasting.
Źródło:
Economic and Regional Studies; 2023, 16, 1; 34-50
2083-3725
2451-182X
Pojawia się w:
Economic and Regional Studies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cuban consumer price index forecasting through transformer with attention
Autorzy:
Rosado, Reynaldo
Toledano-López, Orlando G.
González, Hector R.
Abreu, Aldis J.
Hernandez, Yanio
Powiązania:
https://bibliotekanauki.pl/articles/27314241.pdf
Data publikacji:
2023
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
consumer price index
time series forecasting
transformer with attention
ARIMA
LSTM
Opis:
Recently, time series forecasting modelling in the Con‐ sumer Price Index (CPI) has attracted the attention of the scientific community. Several research projects have tackled the problem of CPI prediction for their countries using statistical learning, machine learning and deep neural networks. The most popular approach to CPI in several countries is the Autoregressive Integrated Mov‐ ing Average (ARIMA) due to the nature of the data. This paper addresses the Cuban CPI forecasting problem using Transformer with attention model over univariate dataset. The fine tuning of the lag parameter shows that Cuban CPI has better performance with small lag and that the best result was in = 1. Finally, the comparative results between ARIMA and our proposal show that the Transformer with attention has a very high performance despite having a small data set.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2023, 17, 2; 12--17
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Enhancing the performance of deep learning technique by combining with gradient boosting in rainfall-runoff simulation
Autorzy:
Abdullaeva, Barno S.
Powiązania:
https://bibliotekanauki.pl/articles/28411647.pdf
Data publikacji:
2023
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
deep learning
gradient boosting
hybrid model
multi-step ahead forecasting
rainfall-runoff simulation
Opis:
Artificial neural networks are widely employed as data mining methods by researchers across various fields, including rainfall-runoff (R-R) statistical modelling. To enhance the performance of these networks, deep learning (DL) neural networks have been developed to improve modelling accuracy. The present study aims to improve the effectiveness of DL networks in enhancing the performance of artificial neural networks via merging with the gradient boosting (GB) technique for daily runoff data forecasting in the river Amu Darya, Uzbekistan. The obtained results showed that the new hybrid proposed model performed exceptionally well, achieving a 16.67% improvement in determination coefficient (R2) and a 23.18% reduction in root mean square error (RMSE) during the training phase compared to the single DL model. Moreover, during the verification phase, the hybrid model displayed remarkable performance, demonstrating a 66.67% increase in R2 and a 50% reduction in RMSE. Furthermore, the hybrid model outperformed the single GB model by a significant margin. During the training phase, the new model showed an 18.18% increase in R2 and a 25% reduction in RMSE. In the verification phase, it improved by an impressive 75% in R2 and a 33.33% reduction in RMSE compared to the single GB model. These findings highlight the potential of the hybrid DL-GB model in improving daily runoff data forecasting in the challenging hydrological context of the Amu Darya River basin in Uzbekistan.
Źródło:
Journal of Water and Land Development; 2023, 59; 216--223
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Financial predictors of corporate insolvency - assessment of the forecast horizon of variables in models of early warning against corporate bankruptcy
Autorzy:
Antonowicz, Paweł
Migdał-Najman, Kamila
Najman, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/25806547.pdf
Data publikacji:
2023
Wydawca:
Szkoła Główna Handlowa w Warszawie
Tematy:
bankruptcy
insolvency
forecasting
financial analysis
early warnings
Opis:
The authors of the study put forward a hypothesis that it is possible to extend the forecast period for the models of discriminant analysis used to assess the risk of enterprise bankruptcy, focusing on the components of these functions in the form of one-dimensional predictors, i.e. the indicators most frequently included in the discriminant functions developed in Poland. Early warning about the growing risk of bankruptcy would be very valuable for any company. The dataset was constructed from all enterprises in Poland that went bankrupt in the years 2007-2013, which was the end of the research project period. Out of the 4,750 business entities that went bankrupt at that time, 2,739 filed financial statements with commercial courts. The main objective was realized using dynamic assessment of the variability of selected one-dimensional predictors of bankruptcy for all of these enterprises. Assessment of the time variability of the indicators under analysis allows conclusions on the predictive possibilities associated with early warning against insolvency of business entities. The results constitute input to the discussion on determination of the longest prognostic horizon that can be adopted in the models of discriminant analysis used to assess the risk of enterprise bankruptcy. Most of them cover an annual forecasting horizon. Only a few authors have attempted to construct models based on data from the two, three, or even four years preceding bankruptcy. The study showed that the main symptoms of the growing risk of bankruptcy in most of the surveyed enterprises are visible much earlier than one year before bankruptcy. This provides an opportunity to correct the predictive models and more time to restructure the company, to prevent bankruptcy. Therefore, the authors of the study have assessed the possibility of extending this forecast period.
Źródło:
e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie; 2023, 101, 4; 39-44
1731-6758
1731-7428
Pojawia się w:
e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting the development of electricity from renewable energy sources in Poland against the background of the European Union countries
Prognozowanie rozwoju energii elektrycznej z odnawialnych źródeł energii w Polsce na tle krajów Unii Europejskiej
Autorzy:
Firlej, Krzysztof Adam
Stanuch, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/24201122.pdf
Data publikacji:
2023
Wydawca:
Fundacja Ekonomistów Środowiska i Zasobów Naturalnych
Tematy:
electricity
forecasting
RES in the European Union
Holt-Winters model
autoregressive model
energia elektryczna
prognozowanie
OZE w Unii Europejskiej
model Holta-Wintersa
model autoregresyjny
Opis:
One of the key elements in the development of countries is energy stability particularly related to ensuring, among other things, continuity of power supply. The European Commission is trying to protect the security of energy supply by introducing internal conditions regarding the share of RES in everyday life. The aim of this article is to forecast the share of RES in electricity production for all the EU member states. The study covers the years 1985-2021, the research is based on two models: the autoregressive (AR) model and the Holt-Winters model, whereas the prediction values were deter-mined for the period 2022-2030. The prediction values showed that Denmark, as the only one of the community countries, may turn out to be self-sufficient in terms of electricity production from RES already at the turn of 2026-2027. In the case of Poland, there is a high probability that the projected RES share for 2030 will not be met. Potentially, for most EU countries, the energy produced from RES will satisfy at least 50% of electricity demand by 2030. A projection of the chances of meeting the commitments presented in the National Energy and Climate Plans regarding the share of renewable energy sources in electricity production in the EU member states in 2030 indicates that they will not be met in most EU economies.
Jednym z kluczowych elementów rozwoju krajów jest stabilność energetyczna szczególnie związana z zapewnieniem ciągłości zasilania, m.in. w energię elektryczną. Komisja Europejska próbuje uchronić bezpieczeństwo dostaw energii wprowadzając wewnętrzne uwarunkowania dotyczące udziału OZE w życiu codziennym. Celem artykułu była prognoza udziału OZE w produkcji energii elektrycznej dla wszystkich krajów członkowskich Unii Europejskiej. Badanie przeprowadzono analizując lata 1985-2021, gdzie badania oparto o dwa modele: autoregresyjny (AR) oraz model Holta-Wintersa, a wartości predykcji zostały wyznaczone dla okresu 2022-2030. Wartości prognoz wykazały, że Dania jako jedyny z krajów wspólnoty już na przełomie 2026-2027 może okazać się państwem samowystarczalnym pod względem produkcji energii elektrycznej z OZE. W przypadku Polski istnieje duże prawdopodobieństwo niespełnienia oczekiwań udziału OZE w planowanym udziale na rok 2030. Potencjalnie, dla większości krajów UE energia produkowana z OZE dla 2030 r. będzie zaspokajać przynajmniej 50% zapotrzebowania na energię elektryczną. Prognoza dotycząca szans realizacji przedstawionych w krajowych planach na rzecz energii i klimatu zobowiązań dotyczących udziału odnawialnych źródeł energii w produkcji energii elektrycznej w krajach członkowskich Unii Europejskiej w 2030 roku wskazuje, że nie zostaną one spełnione w większości gospodarek unijnych.
Źródło:
Ekonomia i Środowisko; 2023, 1; 30--50
0867-8898
Pojawia się w:
Ekonomia i Środowisko
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting the equity premium: Do deep neural network models work?
Autorzy:
Zhou, Xianzheng
Zhou, Hui
Long, Huaigang
Powiązania:
https://bibliotekanauki.pl/articles/23943440.pdf
Data publikacji:
2023
Wydawca:
Fundacja Naukowa Instytut Współczesnych Finansów
Tematy:
equity premium
return predictability
deep neural network
asset allocation
forecasting performance
Opis:
This paper constructs deep neural network (DNN) models for equity-premium forecasting. We compare the forecasting performance of DNN models with that of ordinary least squares (OLS) and historical average (HA) models. The DNN models robustly work best and significantly outperform both OLS and HA models in both in- and out-of-sample tests and asset allocation exercises. Specifically, DNN models generate monthly out-of-sample R2 of 3.42% and an annual utility gain of 2.99% for a mean-variance investor from 2011:1 to 2016:12. Moreover, the forecasting performance of DNN models is enhanced by adding additional 14 variables selected from finance literature.
Źródło:
Modern Finance; 2023, 1, 1; 1-11
2956-7742
Pojawia się w:
Modern Finance
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting the number of road accidents in Poland using weather-dependent trend models
Autorzy:
Gorzelańczyk, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/2203615.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
traffic accident
forecasting
trend model
weather conditions
Opis:
Every year a very large number of people die on the roads. From year to year, the value decreases, there are still a very high number of them. The pandemic has reduced the number of road accidents, but the value is still very high. For this reason, it is necessary to know under which weather conditions the highest number of road accidents occur, and to know the forecast of accidents according to the prevailing weather conditions for the coming years, in order to be able to do everything possible to minimize the number of road accidents. The purpose of the article is to make a forecast of the number of road accidents in Poland depending on the prevailing weather conditions. The research was divided into two parts. The first was the analysis of annual data from the Police statistics on the number of road accidents in Poland in 2001-2021, and on this basis the forecast of the number of road accidents for 2022-2031 was determined. The second part of the research, dealt with monthly data from 2007-2021. Again, the analyzed forecast for the period January 2022-December 2023 was determined. The results of the study indicate that we can still expect a decline in the number of accidents in the coming years, which is particularly evident when analyzing annual data. It is worth noting that the prevailing pandemic distorts the results obtained. The research was conducted in MS Excel, using selected trend models.
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2023, 26(1); 57--76
1505-4675
2083-4527
Pojawia się w:
Technical Sciences / University of Warmia and Mazury in Olsztyn
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Heavy moving average distances in sales forecasting
Autorzy:
Olazabal-Lugo, Maricruz
Espinoza-Audelo, Luis F.
León-Castro, Ernesto
Perez-Arellano, Luis A.
Blanco-Mesa, Fabio
Powiązania:
https://bibliotekanauki.pl/articles/27314242.pdf
Data publikacji:
2023
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
heavy moving average distance
OWA operator
distance measures
sales forecasting
Opis:
This paper presents a new aggregation operator tech‐ nique that uses the ordered weighted average (OWA), heavy aggregation operators, Hamming distance, and moving averages. This approach is called heavy ordered weighted moving average distance (HOWMAD). The main advantage of this operator is that it can use the characteristics of the HOWMA operator to under‐ or over‐ estimate the results according to the expectations and the knowledge of the future scenarios, analyze the his‐ torical data of the moving average, and compare the different alternatives with the ideal results of the dis‐ tance measures. Some of the main families and specific cases using generalized and quasi‐arithmetic means are presented, such as the generalized heavy moving aver‐ age distance and a generalized HOWMAD. This study develops an application of this operator in forecasting the sales growth rate for a commercial company. We find that it is possible to determine whether the company’s objectives can be achieved or must be reevaluated in response to the actual situation and future expectations of the enterprise.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2023, 17, 2; 18--27
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Impact of econometric modeling and perspectives of economic security of the cross-industry complex
Autorzy:
Liezina, Anastasiia
Lavruk, Alexandr
Matviienko, Halyna
Ivanets, Iryna
Tseluiko, Oleksii
Kuchai, Oksana
Powiązania:
https://bibliotekanauki.pl/articles/2201980.pdf
Data publikacji:
2023
Wydawca:
Centrum Badań i Innowacji Pro-Akademia
Tematy:
economic security
intersectoral complex
econometric model
forecasting
bezpieczeństwo ekonomiczne
model ekonometryczny
prognozowanie
Opis:
The paper presents a forecast of the economic security of the inter-industry complex through the construction of a simulation model. The authors considered the possibility of using an econometric model in predicting the level of economic security of the inter-industry complex. The goal was to form a definition of the "inter-industry complex", as well as to study the issues of conceptual and fundamental methods of econometric modeling and forecasting the development of regional industry markets in dynamics. A range of issues related to the main components of economic security in the inter-industry complex has been allocated for scientific work in order to analyze the impact of the components of economic security on the integral indicator. The paper uses a methodology for predicting the structural and spatial-temporal dynamics of interbranch complexes, which includes new and refined methods of modeling and forecasting. As a result, the authors proposed the definition of "inter-industry complex", "economic security in the inter-industry complex", as well as the general provisions of the methodology for econometric modeling and forecasting the level of economic security of the inter-industry complex. The paper presents a full-scale simulation model that allows you to set, evaluate and make a decision using large nonlinear data. This kind of system contains dynamic and retarded data, which makes it possible to apply econometric modeling in automatic calculation.
Źródło:
Acta Innovations; 2023, 47; 73--83
2300-5599
Pojawia się w:
Acta Innovations
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Impact of information on the number of traffic accidents on the outcome of the forecast
Autorzy:
Gorzelanczyk, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/22672802.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
forecasting
traffic accident
number of time series elements
mean absolute percentage error MAPE
Opis:
Every year, more and more vehicles appear on the world's roads. This leads to increased traffic on the roads. Road accidents have become a rapidly growing threat. They cause loss of human life and economic assets. This is due to the rapid growth of the world's human population and the very rapid development of motorization. The main problem in forecasting and analyzing data on the number of traffic accidents is the small size of the dataset that can be used for analysis in this regard. And on the other hand, road accidents cause, globally, millions of deaths and injuries annually is their density in time and space. It is worth noting that the pandemic has reduced the number of traffic accidents. However, the value is still very high. The purpose of the article is to assess the impact of information on the number of traffic accidents on the outcome of the forecast. To this end, using historical statistical data, the forecast of the number of traffic accidents for the following years was determined, and how this variability of the input data affects the value of the average percentage error of the forecast was determined. Based on the study, it can be concluded that a smaller number of input data, historical data on the number of accidents, instead of 32 years, 7 years, makes the determination of the forecast of the number of accidents for subsequent years, is at a satisfactory level, the average absolute percentage error of MAPE less than 7%. The article concludes with the determination of the forecast for future years. It is worth noting that the prevailing pandemic distorts the results obtained.
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2023, 26(1); 219--230
1505-4675
2083-4527
Pojawia się w:
Technical Sciences / University of Warmia and Mazury in Olsztyn
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improving national strategic foresight with the use of forecasting tournaments and its implications for the study of international relations
Autorzy:
Kleňha, Jan
Powiązania:
https://bibliotekanauki.pl/articles/31343765.pdf
Data publikacji:
2023-07-26
Wydawca:
Uniwersytet Warszawski. Wydział Nauk Politycznych i Studiów Międzynarodowych
Tematy:
national strategy
foresight
forecasting tournament
Delphi method
deliberation
prediction
consensus
Opis:
Improving national strategic foresight can help the formation of more robust and informed policies, including foreign policy. Predicated upon the theory behind peer-prediction elicitation methods such as Reciprocal Scoring, we combined two foresight methods - Forecasting tournaments and a Delphi method - into a design in which a forecasting tournament predicted the results of a Delphi. Experts in a Delphi could take into account the arguments of participants from a prior forecasting tournament and thus make better-informed decisions. This methodological article aims to validate the feasibility of this design. It describes how we implemented it for identifying and prioritizing global megatrends as part of a strategic foresight project for the Czech government. We found this design practically applicable, while the forecasting tournament also seems to improve the ability of participants to predict a group consensus. Similar combinations of foresight methods could be used to enhance the study of international relations.
Źródło:
Stosunki Międzynarodowe - International Relations; 2021, 57; 71-92
0209-0961
Pojawia się w:
Stosunki Międzynarodowe - International Relations
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Loadability maximisation in bilateral network for real-time forecasting system using cuckoo search algorithm
Autorzy:
Venkatasivanagaraju, S.
Rao, M. Venkateswara
Powiązania:
https://bibliotekanauki.pl/articles/38699704.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
optimal power flow
NR method
short-term load forecasting
long-term load forecasting
cuckoo search algorithm
optimisation
loss minimisation
optymalny przepływ mocy
metoda NR
krótkoterminowe prognozowanie obciążeń
długoterminowe prognozowanie obciążeń
algorytm kukułki
optymalizacja
minimalizacja strat
Opis:
This manuscript proposes an optimal power flow (OPF) solution in a coordinated bilateralpower network. The primary goal of this project is to maximise the benefits of the powermarket using Newton–Raphson (NR) and cuckoo search algorithm CSA methodologies.The global solution is found using a CSA-based optimisation approach. The study isconducted on real-time bus system. To avoid this, creative techniques have lately beenused to handle the OPF problem, such as loadability maximisation for real-time predictionsystems employing the CSA. In this work, cuckoo search (CS) is used to optimise theobtained parameters that help to minimise parameters in the predecessor and consequentunits of each sub-model. The proposed approach is used to estimate the power load in thelocal area. The constructed models show excellent predicting performance based on derivedperformance. The results confirm the method’s validity. The outcomes are compared withthose obtained by using the NR method. CSA outperformed the other methods in thisinvestigation and gave more accurate predictions. The OPF problem is solved via CSAin this study. Implementing a real-time data case bus system is recommended to test theperformance of the established method in the MATLAB programme.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 73-88
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 624

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