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Wyniki wyszukiwania dla: energy forecasting
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The investment risk forecasting in a local energy market
PublikacjaThe paper considers the general problems faced when evaluating the risk of investing in a local energy market by computer tools. The proposal formulated for the emerging local energy markets suggests broadening the method of evaluating investment risk so as to include elements of cluster analysis. The paper also discusses the significance of estimating investment risk in market terms and the importance and range of the local energy...
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Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan
PublikacjaThis paper examines the usefulness of statistical methods in forecasting the financial energy of households. The study’s objective is to create the innovative ratios that combine both financial and demographic information of households and implement them in the forecasting models. To conduct this objective, six forecasting models are developed using three different methods—discriminant analysis, logit analysis, and decision trees...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Optimization of Division and Reconfiguration Locations of the Medium-Voltage Power Grid Based on Forecasting the Level of Load and Generation from Renewable Energy Sources
PublikacjaThe article addresses challenges in optimizing the operation of medium voltage networks, emphasizing optimizing network division points and selecting the best network configuration for minimizing power and energy losses. It critically reviews recent research on the issue of network configuration optimization. The optimization of the medium voltage power grid reconfiguration process was carried out using known optimization tools....
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
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Effective Short -term Forecasting of Wind Farms Power
PublikacjaForecasting a specific wind farm's generation capacity within a 24 hour perpective requires both a reliable forecast of wind, as well as supporting tools. This tool is a dedicated model of wind farm power. This model should include not only general rules of wind to mechanical energy conversion, but also the farm's specific features. This paper present analytical, statistical, and neuron models of wind farm power. The study is based...
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High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events
PublikacjaDischarge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River....
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Selected Aspects of Biofuels Market and the Electromobility Development in Poland: Current Trends and Forecasting Changes
PublikacjaThis work presents basic information associated with markets of selected alternative fuels used in transport, such as methyl esters, conventional bioethanol and lignocellulosic bioethanol, and the market of electrical vehicles. Legal conditions, which stimulate development and regulate the mode of functioning of the liquid biofuel market until 2020 are discussed, based on provisions of EU directives. Data on biofuel production...
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Hybrid Inception-embedded deep neural network ResNet for short and medium-term PV-Wind forecasting
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Hybrid forecasting models for wind-PV systems in diverse geographical locations: Performance and power potential analysis
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Development of the Polish energy sector through transformation and harmonization with the European energy and climate policy
PublikacjaThe paper presents the dilemmas of energy sector development vs European energy policy due to the way of energy transition. The identification of barriers and opportunities for the development of the power industry is presented. The possibilities of using modern energy technologies for the processes of energy transformation are described. The path useful to achieving climate and energy goals is determined. The new method of electricity...
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FORECASTING ELECTRICITY PRICES IN POLAND
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FORECASTING BIOGAS FORMATION IN LANDFILLS
Publikacja: The aim of the present research was to develop a mathematical model for estimating the amount of viscous gas generated as a function of weather conditions. Due to the lack of models for predicting gas formation caused by sudden changes in weather conditions in the literature, such a model was developed in this study using the parameters of landfills recorded for over a year. The effect of temperature on landfill gas production...
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Forecasting risks and challenges of digital innovations
PublikacjaForecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...
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A fuzzy logic model for forecasting exchange rates
PublikacjaThis article is devoted to the issue of forecasting exchange rates. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology - fuzzy logic theory - and to evaluate its effectiveness in times of prosperity and during the financial crisis. The model is based on sets of rules written by the author in the form of IF-THEN, where expert knowledge is stored. This model is the result...
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The Implementation of Fuzzy Logic in Forecasting Financial Ratios
PublikacjaThis paper is devoted to the issue of forecasting financial ratios. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology, i.e., fuzzy logic theory, and to evaluate its effectiveness. Fuzzy logic has been widely used in machinery, robotics and industrial engineering. This paper introduces the use of fuzzy logic for the financial analysis of enterprises. While many current...
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Forecasting of retail prices of liquid fuels in Poland
PublikacjaMotivation: In recent years, the prices of liquid fuels in Poland have been rising , negatively affecting the country’s economy and the daily life of its inhabitants. Consequently, there is a need for effective forecasting of prices in fuel markets, as this could enable entrepreneurs and consumers to make more informed decisions. Aim: The objective of the article was to forecast the retail prices of EU95 petrol and diesel fuel...
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Forecasting of fatigue life of laser welded joints
PublikacjaW pracy przedstawiono podstawowe dane na temat stalowych paneli typu sandwich. Zaprezentowano wyniki testów zmęczeniowych elementarnych połączeń teowych spawanych laserowo. Omówiono szczegółowo te cechy, które mają istotny wpływ na statyczne i zmęczeniowe własności złącza. Na podstawie przedstawionych wyników badań zmęczeniowych elementarnych połączeń spawanych laserowo uzyskano krzywą projektową S-N dla jednego z pokazanych modeli...
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Forecasting of the Employment Rate in the EU ICT Field
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Increasing rail life by forecasting fatigue failure.
PublikacjaReferat poświęcony jest przedłużaniu żywotności szyn i obejmuje zagadnienia prognozowania liczby pęknięć a także planowania szlifowań szyn. Dane pomiarowe pochodzą z wieloletnich badań przeprowadzonych w Katedrze Inżynierii Kolejowej Politechniki Gdańskiej na liniach magistralnych PKP.
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Evaluation of the Macro- and Micro-Economic Factors Affecting the Financial Energy of Households
PublikacjaThis paper is an evaluation of the common macro-economic, micro-economic, and social factors affecting households’ financial situations. Moreover, the author’s objective was to develop a fuzzy logic model for forecasting fluctuations in the number of nonperforming consumer loans in a country using the example of Poland. This study represents one of the first attempts in the global literature to develop such a forecasting model...
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The Dynamics of Trade Relations between Ukraine and Romania: Modelling and Forecasting
PublikacjaThe article examines the monthly dynamics of exports, imports and balance of trade between Ukraine and Romania in the period from 2005 to 2021. Time series from 2015 to 2021 were used for modelling and forecasting (since the date the European Union–Ukraine Association Agreement took effect). Adequate models of the dynamics series of the Box-Jenkins methodology were built: additive models with seasonal component ARIMA (Autoregressive...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublikacjaThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Application of Bayesian Networks for Forecasting Future Model of Farm
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Application of dynamic factor models for inflation forecasting in Poland
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Estimating and Forecasting GDP in Poland with Dynamic Factor Model
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An innovative approach to the forecasting of energetic effects while wood sawing
PublikacjaIn 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, the cutting forces (power) problem may be tackled with an innovative, up-to-date fundamental analysis of the mechanics of sawing based on modern fracture...
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An Innovative Approach to the Forecasting of Energetic Effects While Wood Sawing
PublikacjaIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specifi c cutting resistance, which is in the case of wood cutting the function of more or less important factors. On the other hand, the cutting forces (power) problem may be tackled with an innovative, up-to-date fundamental analysis of the mechanics of sawing based on modern fracture mechanics....
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Examining Ownership Equity as a Psychological Factor on Tourism Business Failure Forecasting
PublikacjaThis paper examines ownership equity as a predictor of future business failure within the tourism and hospitality sectors. The main goals of this study were to examine which ratios are the most important for a tourism business failure forecasting model and how significant is the “total percentage of equity ownership by company directors” ratio compared with other ratios associated with the probability of bankruptcy. A stepwise...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublikacjaResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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FORECASTING EXCHANGE RATES IN THE PROCESS OF THE ASSESSMENT OF CONSUMER RISK BANKRUPTCY IN CENTRAL EUROPE
PublikacjaThis paper focuses on the issue of forecasting the fluctuation of exchange rates as part of the early warning system against the risk of consumer bankruptcy. The author identified the main macroeconomic factors affecting the level of bankruptcies for households in Poland. The fluctuation of exchange rates, which directly affects the deterioration of the economic situation of borrowers who have opened credit accounts in a foreign...
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Forecasting of currency exchange rates using artificial neural networks
PublikacjaW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Forecasting demand for products in distribution networks using R software
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The original method of cutting power forecasting while wood sawing
PublikacjaEfekty energetyczne procesu przecinania drewna piłami (siły skrawania i moc skrawania) przy klasycznym podejściu do zagadnienia są określane na podstawie wartości właściwego powierzchniowego oporu skrawania. Z drugiej strony siły skrawania można rozważać z punktu widzenia współczesnej mechaniki pękania. Prognozowanie wartości kąta ścinania z zastosowaniem modeli uwzględniających wiązkość materiału obrabianego, ścinanie w płaszczyźnie...
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Upper Limb Bionic Orthoses: General Overview and Forecasting Changes
PublikacjaUsing robotics in modern medicine is slowly becoming a common practice. However, there are still important life science fields which are currently devoid of such advanced technology. A noteworthy example of a life sciences field which would benefit from process automation and advanced robotic technology is rehabilitation of the upper limb with the use of an orthosis. Here, we present the state-of-the-art and prospects for development...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Multi-factor fuzzy sets decision system forecasting consumer insolvency risk
PublikacjaThe objective of this study is to develop a multi-factor decision system predicting insolvency risk for natural persons with the use of fuzzy sets. Considering that the financial situation of households is affected by various endogenous and exogenous factors, the main assumption of this study is that the system for predicting financial difficulties should not be limited to the use of only a few financial variables concerning consumers,...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublikacjaTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Forecasting of railway track tamping based on settlement of sleepers using fuzzy logic
PublikacjaThe sleepers in a railway track transfer vertical, transverse and longitudinal loads to the track ballast and subgrade. The sleepers allow for keeping the distance between the rails constant. The thickness of ballast should be between 16 and 35 cm depending on the design standard of the track, and it should be densified where the ballast supports the sleeper. The exploitation causes contamination of the ballast, crushing the material...
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Application of road map of operating condition for estimation of fuel and electric energy consumption from city transport
PublikacjaThe paper presents procedure of data collecting and generation of road map of operating condition in the selected urban area. This map allows forecasting the selected vehicle operating parameters for the assumed road. The main parameters calculated using the road maps of operating conditions are: total energy spent to drive the selected vehicle, consumed fuel, travel time, average speed of travel, CO2 emissions. Presented example...
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Hydrological Forecasting in the Oder Estuary using a Three- Dimensional Hydrodynamic Model
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The influence of electromagnetic pollution on living organisms – historical trends and forecasting changes
PublikacjaCurrent technologies have become a source of omnipresent electromagnetic pollution from generated electromagnetic fields and resulting electromagnetic radiation. In many cases this pollution is much stronger than any natural sources of electromagnetic fields or radiation. Wireless and radio communication, electric power transmission or devices in daily use such as smartphones, tablets and portable computers every day expose people...
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Artificial-Hand Technology—Current State of Knowledge in Designing and Forecasting Changes
PublikacjaThe subject of human-hand versatility has been intensively investigated for many years. Emerging robotic constructions change continuously in order to mimic natural mechanisms as accurately as possible. Such an attitude is motivated by the demand for humanoid robots with sophisticated end effectors and highly biomimic prostheses. This paper provides wide analysis of more than 80 devices that have been created over the last 40 years....
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High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model
PublikacjaDue to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model....
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Application of time-series-cross-section data in case of sale forecasting in an enterprise
PublikacjaW artykule wskazano możliwości wykorzystania danych przestrzenno-czasowych do prognozowania sprzedaży w przedsiębiorstwie. Przedstawiono różne podejścia do prognozowania ekonometrycznego przy użyciu tego typu danych. Wyznaczono krótkookresowe prognozy sprzedaży benzyny bezołowiowej Pb95 w przekroju województw oraz dokonano oceny ich jakości przy użyciu mierników ex-post. Dwie najdokładniejsze metody prognozowania wykorzystano do...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...