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Search results for: forecasting
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Neuroeconomy and Neuromarketing: The Study of the Consumer Behaviour in the COVID-19 Context
PublicationTo address the study of consumer behavior in the post-COVID-19 era, the present Research Topic brings together a set of papers that attempt to study how different factors triggered by the pandemic have achieved a significant effect on consumers' behavioral intentions. These papers examine different subtopics related to food, health products, collaborative economy and, of course, neuroscience. Globally, the objectives of this special...
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Modeling process of planning finished product sales volumes at industrial enterprises in modern economic conditions
PublicationThis article presents improving the existing system of planning finished products sales volumes. The influencing factors of the sales volumes in modern economic conditions have been determined: falling world oil prices, the reduction of pipe consumption in the domestic market, the global pandemic. The algorithm of planning finished products sales volumes has been constructed. Calculations based on the Holt forecasting method has...
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Application of fracture mechanics for energetic effects predictions while wood sawing
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. On the other hand, cutting forces (power) could be considered from a point of view of modern fracture mechanics. Cutting forces may be employed to determine not only toughness...
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Estimation of fracture toughness and shear yield stress of orthotropic materials in cutting with rotating tools
PublicationThe cutting force is an energetic effect of splitting material, and might be considered from a point of view of modern fracture mechanics. Forecasting of the shear plane angle in cutting broaden possibilities for modelling of the cutting process even for thin uncut chips. Such mathematical model has been developed here for description of the orthotropic materials’ cutting on the base of fracture theory, and includes work of separation...
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Idea zastosowania sztucznej inteligencji w prognozowaniu wpływu drgań komunikacyjnych na odpowiedź dynamiczną budynków mieszkalnych
PublicationW poniższym artykule autorzy analizują wpływ drgań komunikacyjnych na budynki mieszkalne oraz metodykę pomiarową według PN-85 B-02170 [1]. Problemem badawczym jest opracowanie prostej metody prognozowania wpływu drgań na budynki mieszkalne w taki sposób, aby nie było konieczne przeprowadzanie pracochłonnych i kosztownych pomiarów polowych. W tym celu wykonano analizę przy użyciu algorytmów opartych na sztucznej inteligencji oraz...
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Application of Fracture Mechanics for Energetic Effects Predictions While Wood Sawing
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. On the other hand, cutting forces (or power - more interesting from energetic point of view) could be considered from a point of view of modern fracture mechanics. Cutting...
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SAWING PROCESS AS A NEW ALTERNATIVE WAY OF DETERMINING SOME WOOD PROPERTIES
PublicationCutting forces (power) could be considered from a point of view of modern fracture mechanics. The developed cutting model, derived from fracture mechanics, includes work of separation (fracture toughness) in addition to plasticity and friction, and also dullness of the cutting edge described by the cutting edge radius. Moreover, forecasting of the shear plane angle for the cutting models, broaden possibilities of energetic effects...
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Predicting cutting power for band sawing process of pine and beech wood dried with the use of four different methods
PublicationWood drying is an important stage in the woodworking process. After drying, wood is subject to a re-sawing process, for which a high quality surface, low material loss, and high efficiency are often required. In this paper, forecasted values were presented of cutting power for the re-sawing process of pine and beech wood that were dried with four different methods. Forecasting of cutting power for an industrial band saw machine...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublicationLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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AN ALTERNATIVE WAY OF DETERMINING MECHANICAL PROPERTIES OF WOOD BY MEASURING CUTTING FORCES
PublicationThe cutting force is an energetic effect of splitting material, and might be therefore considered from a point of view of modern fracture mechanics. The dedicated mathematical model developed for description of the wood cutting has been developed here on the base of fracture theory, and includes work of separation (fracture toughness) in addition to the material plasticity and friction. The effect of the cutting edge dullness is...
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Creating Polish space language dictionary - lessons learned
PublicationPolish space industry suffers from lack of space vocabulary. Since joining European Space Agency in 2012, the sector has expanded rapidly now employing over 1000 specialists focusing mainly on space sustainability, space debris detection and tracking, robotics and propulsion systems. The Polish Space Agency together with The Polish Committee for Standardization have committed to creating the first lexicon of space language, along...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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A unified approach to the analysis of electric energy and fuel consumption of cars in city traffic
PublicationForecasting fuel and electricity consumption is an important factor determining the direction of changes in road engineering solutions, traffic management, selection of routes for public transport and development more efficient car drive systems. With a reliable and easy-to-use computational tool, it is possible to reduce the consumption of primary energy sources and reduce the emission of toxic compounds in cities. An analysis...
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Dependence of Housing Real Estate Prices on Inflation as One of the Most Important Factors: Poland’s Case
PublicationThe study aimed to examine the impact of inflation on the real estate market using Polish panel data for the last 13 years. It is based on a panel model, where price changes of one square meter of housing are determined as a function in changes of inflation, the central bank's base rate, dwellings built, as well as new mortgage loans. The quarterly dynamics of the average price of 1 square meter of housing in...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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AI-Driven Sustainability in Agriculture and Farming
PublicationIn this chapter, we discuss the role of artificial intelligence (AI) in promoting sustainable agriculture and farming. Three main themes run through the chapter. First, we review the state of the art of smart farming and explore the transformative impact of AI on modern agricultural practices, focusing on its contribution to sustainability. With this in mind, our analysis focuses on topics such as data collection and storage, AI...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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The Dilemmas of Choosing a Suitable Technology for Low Energy and Passive Houses in the Context of their Overheating Issues
PublicationIn compliance with European Union directives, numerous countries are introducing increasingly stricter legal limits on the estimated energy consumption of newly designed residential buildings. However, the fact, that regulations and designers' efforts are focused on decreasing energy consumption (and consequently carbon dioxide emissions) only at the post-occupancy stage, may lead to a significant increase in the carbon footprint...
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Experiences and Challenges in Fatality Reduction on Polish Roads
PublicationAccording to the UN, road safety is the key to achieving sustainable development goals, yet the complexity of how road accidents happen makes this a difficult challenge leaving many countries struggling with the problem. For years, Poland has infamously been one of the EU’s top countries for road-accident fatality rates. Despite that, it has made significant progress in the last thirty years with a fatality reduction of more than...
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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries
PublicationIn developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is....
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Quality assessment of low voltage surge arresters
PublicationUsers expect reliable operation of the surge arrester during overvoltages, which may originate from a switching process or a lightning discharge. The necessary conditions to guarantee these expectations are: appropriate construction of the surge arrester, its production being maintained in accordance with technical standards, and a positive results of the type test (as well routine and acceptance tests). The recipient, especially...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Wybrane wyniki badań potrzeb transportowych mieszkańców województwa pomorskiego
PublicationNa potrzeby opracowania Planu Zrównoważonego Rozwoju Publicznego Transportu Zbiorowego Województwa Pomorskiego w czwartym kwartale 2013 roku konsorcjum Fundacji Rozwoju Inżynierii Lądowej oraz z Politechniki Gdańskiej wykonało badania potrzeb transportowych mieszkańców województwa pomorskiego oraz wielkości popytu na usługi przewozowe. Uzyskane wyniki były podstawą do budowy transportowego modelu symulacyjnego podróży realizowanych...
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DESIGN LOGICAL LINGUISTIC MODELS TO CALCULATE NECESSITY IN TRUCKS DURING AGRICULTURAL CARGOES LOGISTICS USING FUZZY LOGIC
Publication: The study is aimed to develop the logic-linguistic models to design a number of rules for the correct calculation of the vehicles needed, taking into account the technical, technological, and weather and climate conditions of the harvesting and transport complex. The article has shown that the construction of the design of logic-linguistic models was not performed earlier to solve the problem of the agro-industrial production...
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The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017
PublicationPrecise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublicationThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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Skuteczne prognozowanie krótkoterminowe mocy farm wiatrowych
PublicationPrognozowanie mocy wytwórczej konkretnej farmy wiatrowej (FW) w horyzoncie 24-godzinnymwymaga zarówno wiarygodnej prognozy wietrzności, jak i narzędzi wspomagających. Narzędzie to jest dedykowanym modelem mocy farmy. Model powinien uwzględniać nie tylko ogólne zasady przetwarzania energii wiatru na energię mechaniczną, ale także cechy szczególnekonkretnej farmy. Liczba czynników wpływających na moc farmy jest duża i dokładna prognozamocy,...
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Ruchotwórczość wielkopowierzchniowych obiektów handlowych trzeciej generacji na przykładzie Trójmiasta
PublicationWielkopowierzchniowe obiekty (handlowe, usługowe itp.) generują ruch o dużych natężeniach, które często przekraczają możliwości przepustowe przyległego układu ulicznego. Wpływają w ten sposób na znaczne pogorszenie się warunków ruchu w najbliższym otoczeniu obiektu i zakłócenia w prawidłowym funkcjonowaniu systemu transportowego miasta. Wobec braku polskich doświadczeń konieczne jest badanie wpływu wybranych czynników demograficznych,...
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Assessment of the ice jam potential on regulated rivers and reservoirs with the use of numerical model results
PublicationThis study presents an attempt at estimating the jam potential on rivers with significant anthropogenic intervention in the course or flow characteristics of the river. The DynaRiCE model was used for forecasting both the place and time of an ice jam occurrence. In this modified method, two ice parameters are subjected to analysis, namely the relative ice-to-water velocity (vi/vw),and the ice thickness to single floe thickness...
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Systematic Assessment of Product Quality
PublicationThe article describes an innovative metrizable idea for systemic assessments of product quality within the baking industry. Complex product quality analysis requires the employment of metrizability criteria for factors that impact the quality of the product, and these are called determinants. Therefore, such analysis is only possible with the use of systems engineering. A system represents the potential of a manufacturing process,...
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Predicting bankruptcy with the use of macroeconomic variables
PublicationRegarding the current global financial crisis, the firms can expect the increased uncertainty of their existence. The relevant literature includes extensive studies on bankruptcy prediction. Studies show that the most popular method used for prediction of firms' failures are discriminant analyses (30,3% of all models), then logit and probit models (21,3%), which all three are parametric models. The nature, the structure of the...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublicationDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Metoda obliczania skutków wdrożenia strategii zarządzania popytem na energię elektryczną (DSM/DSR) w systemach elektroenergetycznych
PublicationW niniejszej rozprawie poruszono zagadnienie strategii zarządzania popytem na energię elektryczną (DSM/DSR) i sposobów obliczania efektów ich wdrożenia. W związku z tym opisano oczekiwane efekty wdrożenia tych rozwiązań oraz ich zalety i wady. Zaprezentowano i przeanalizowano istniejące już metody obliczania skutków wdrożenia DSM/DSR. Zaproponowano nową metodę, która poprzez formę algorytmu uporządkowuje proces obliczania i oceny...
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Modelowanie podziału zadań przewozowych w obszarach zurbanizowanych
PublicationNiniejsza rozprawa doktorska dotyczy problematyki modelowania podziału zadań przewozowych w procesie modelowania podróży. Wykonane analizy wykazały zasadność zastosowania dodatkowych czynników w modelowaniu wyboru środka transportu z uwagi na ich istotny wpływ na jakość modelu dla wybranych motywacji podróży. W pracy zawarto przykładowe modele uwzględniające każdy z analizowanych czynników. Z wykorzystaniem badań heurystycznych...
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Wykorzystanie analizy kosztów w zarządzaniu szpitalem publicznym
PublicationProblemy z finansowaniem opieki zdrowotnej obserwowane są praktycznie na całym świecie. Jako przyczyny wzrostu wydatków uważa się głównie starzenie się populacji, złożoną naturę współczesnych chorób i szerokie wykorzystywanie kosztownych technologii. Systemy opieki zdrowotnej na całym świecie stają przed trudnym wyzwaniem zwiększenia efektywności, co oznacza kontrolowanie kosztów, przy jednoczesnym zapewnieniu wysokiej jakości...
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Assessing and Mitigating Ice-Jam Flood Hazards and Risks: A European Perspective
PublicationThe assessment and mapping of riverine flood hazards and risks is recognized by many countries as an important tool for characterizing floods and developing flood management plans. Often, however, these management plans give attention primarily to open-water floods, with ice-jam floods being mostly an afterthought once these plans have been drafted. In some Nordic regions, ice-jam floods can be more severe than open-water floods,...
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NUMERYCZNE MODELOWANIE HYDRODYNAMIKI JAKO NARZĘDZIE WSPOMAGANIA PROJEKTOWANIA REKREACYJNYCH I SPORTOWYCH OBIEKTÓW WODNYCH
PublicationW artykule opisano zastosowanie obliczeń numerycznych w procesie projektowania, analizy działania oraz oceny bezpieczeństwa użytkowania wodnych obiektów rekreacyjnych i sportowych. Użytkownicy aquaparków, sportowcy, a szczególnie kibice, oczekują wyjątkowych doznań na obiektach wodnych z jednoczesną gwarancją bezpieczeństwa. Na te kwestie duży wpływ ma hydrodynamika przepływu. Aby właściwie dobrać parametry geometryczne i hydrauliczne...
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Prognozowanie właściwości złączy spawanych pod wodą metodą lokalnej komory suchej
PublicationNiniejsza praca jest poświęcona spawaniu pod wodą metodą lokalnej komory suchej (MLKS) i przedstawia metodologię oraz narzędzia umożliwiające prognozowanie właściwości złączy spawanych wykonanych przy zastosowaniu tej odmiany spawania. Monografia zawiera opis rozwoju spawania pod wodą oraz charakterystykę metod wykorzystywanych do realizacji prac spawalniczych. Zaproponowano nowy podział metod spawania pod wodą, uwzględniający...
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ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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Equilibrium price - modelling, forecast and application
PublicationNowoczesną gospodarkę charakteryzuje wzrastające znaczenie cen. Znajomość ogólnych zasad mechanizmu kształtującego ceny oraz analizy cen umożliwiają przedsiębiorstwom przewidzenie ceny równowagi i podjęcie przynoszącej zyski decyzji, zwłaszcza na rynku oligopolu homogenicznego, gdzie przedsiębiorcy muszą brać pod uwagę reakcję konkurencji. Przedstawiony w artykule, dynamiczny model ekonometryczny cen benzyny, na rynku paliw płynnych...
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Scenarios in the development strategies of larger cities in Poland
PublicationSummary: Planning prepares decisions and future actions. Therefore, future conditions should be considered in planning, in particular strategic planning, due to its long-term nature. To accomplish this, certain prognostic methods should be applied. A scenario method is seen as one of the most useful prognostic method, especially in cases when social and institutional behaviour plays a crucial role. The aim of the paper is an analysis...
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Scenarios in regional planning – theory and practice in Poland
PublicationAbstract. It is important to recognise future conditions in planning because it primes future actions. Scenarios are useful prognostic tools, especially when the social and institutional behaviour plays a crucial role. The aims of the paper are: (1) to indicate the roles and the place of scenarios in the strategic plan building process; (2) to analyse and evaluate the application of scenarios in regional planning in Poland; (3)...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublicationThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Times Series Analysis Of Road Safety Trends At The Regional Level In Poland
PublicationThe paper presents possibility of applying a structural times series modeling with explanatory and intervention variables as a tool capable for explaining the changes in the monthly number of fatalities and seriously injured in traffic accidents. The analysis covers regional level and takes into consideration traffic accidents data of two regions: Pomorskie and Warmia-Mazury. In addition short-term forecasts for the two regions...
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Ionosphere variability II: Advances in theory and modeling
PublicationThis paper aims to provide an overview on recent advances in ionospheric modeling capabilities, with the emphasis in the efforts relevant to electron density variability. The discussion spans a wide range of model formulations (e.g., from purely empirical to physics-based ones and data-driven approaches) seeking for advances or gaps with regard to present challenges. This discussion is further supported by consideration of the...