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Search results for: TIME-SERIES MODELING
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TIME SERIES MODELING (PG_00063724)
e-Learning CoursesEffectively uses in-depth knowledge of economic time series analysis methods, applying the results of analyzes to formulate forecasts. Subject contents: 1. Classical time series analysis (trend, cyclical fluctuations) 2. Exponential smoothing models 3. Holt and Winters model 4. Stochastic processes and time series 5. Characteristics of stochastic processes 6. Process spectrum autocorrelation functions 7. Study of the stationarity...
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TIME SERIES MODELING 2023/2024
e-Learning Coursesprowadzący: assoc. prof. Ján Dvorský, PhD
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Testing Topological Conjugacy of Time Series
PublicationThis paper considers a problem of testing, from a finite sample, a topological conjugacy of two trajectories coming from dynamical systems (X, f ) and (Y, g). More precisely, given x1, . . . , xn \subset X and y1, . . . , yn \subset Y such that xi+1 = f (xi) and yi+1 = g(yi) as well as h : X \rightarrow Y, we deliver a number of tests to check if f and g are topologically conjugated via h. The values of the tests are close to...
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Investigation of noises in the EPN weekly time series
PublicationThe constantly growing needs of permanent stati ons’ velocities users cause their stability level to increase. To this research we included more than 150 stations located across Europe operating within the EUREF Permanent Network (EPN) w ith weekly changes in the ITRF2005 reference frame. The obvious long-range dependencies in the stochastic part of GPS time series were p roven by Ljung-Box...
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TIME SERIES DATA FOR 3D FLOOD MAPPING
PublicationThanks to the ability to collect information about large areas and with high frequency in time areas threatened by floods can be closely monitored. The effects of flooding are socio-economic losses. In order to reduce those losses, actions related to the determination of building zones are taken. Moreover, the conditions to be met by facilities approved for implementation in such areas are determined. Therefore, satellite data...
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Short-Period Information in GPS Time Series
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Traffic risk modelling using time-series
PublicationW referacie przedstawiono metodę prognozowania ryzyka w ruchu drogowym powstałą na bazie analizy szeregów czasowych. W jej oparciu dla danych o liczbie śmiertelnych ofiar wypadków drogowych w Polsce w latach 1989-2000 zbudowano model i wykonano prognozę rozwoju trendu w przyszłości.
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Traffic fatalities modelling using time-series.
PublicationReferat zawiera opis jednaj z metod analizowania trendów bezpieczeństwa ruchu drogowego opartej na teorii szeregów czasowych. Przedstawiono w nim aplikację tej metody do badania związku pomiędzy liczbą śmiertelnych ofiar wypadków drogowych w Polsce w latach 1991-2003 a wielkością bezrobocia w tym czasie.
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Time series - the tool for traffic safety analysis
PublicationGłównym celem artykułu jest przedstawienie sposobu modelowania i modeli stosowanych w analizach i prognozowaniu odnośnie zmian śmiertelności w wypadkach drogowych w Polsce. W tym celu zastosowano teorię modeli strukturalnych szeregów czasowych przy założeniu, że zarówno ruch drogowy, jak i bezpieczeństwo na drogach są procesami dynamicznymi, w których przeszłość ma znaczący wpływ na teraźniejszość i przyszłość systemu.
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Entropy of Financial Time Series Due to the Shock of War
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Journal of Time Series Econometrics
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JOURNAL OF TIME SERIES ANALYSIS
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Irregular variations in GPS time series by probability and noise analysis
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Modeling SPMD Application Execution Time
PublicationParallel applications in a Single Process Multiple Data paradigm assume splitting huge amounts of data to multiple processors working in parallel at small data packets. As the individual data packets are not independent, the processors must interact with each other to exchange results of the calculations with their adjacent partners and take these results into account in their own computations. An example of SPMD is geometric parallelism...
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Modeling DAC Application Execution Time
PublicationAn application written in the Divide And Conquer paradigm is more difficult to model than SPMD application because of complex algorithm, causing use of many coefficients in a computational complexity function. Processors are divided into various layers, each layer contains different number of processors. Data packets processed in different layers and transferred between layers have different length. Moreover first layer processors use...
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Road safety analysis in Poland using time-series modelling techniques
PublicationA number of international studies argue that there is a correlation between the number of traffic fatalities and the degree of public activity. The studies use the unemployment rate to support that argument. As unemployment grows miles travelled fall, a factor known to affect road safety. This relationship seems to be true for Poland, as well. The model presented in the paper is intended to prove it. It is a structural time-series local...
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On the Handling of Outliers in the GNSS Time Series by Means of the Noise and Probability Analysis
PublicationThe data pre-analysis plays a significant role in the noise determination. The most important issue is to find an optimum criterion for outliers removal, since their existence can affect any further analysis. The noises in the GNSS time series are characterized by spectral index and amplitudes that can be determined with a few different methods. In this research, the Maximum Likelihood Estimation (MLE) was used. The noise amplitudes...
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Application of PCA and time series analysis in studies of precipitation in Tricity (Poland).
PublicationPrzedstawiono wyniki monitoringu zanieczyszczenia atmosfery Trójmiasta. Próbki wody opadowej pobierano w cyklach miesięcznych przez 4 lata (1998-2001)w 10 punktach. Wyniki poddano statystycznej i chemometrycznej analizie (szeregi czasowe, analiza wariancji, analiza głównych składowych). Wykazano wpływ lokalizacji punktów monitoringowych i bliskości Morza Bałtyckiego na zawartość jonów nieorganicznych w analizowanych próbkach.
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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Autocovariance based weighting strategy for time series prediction with weighted LS-SVM
PublicationPrzedstawiono metodę konstrukcji algorytmów z funkcją jądra, a także dwa algorytmy uzyskane poprzez użycie różnych funkcji straty. Zaproponowano kowariacyjną strategię ważenia algorytmów z kwadratową funkcją straty do problemu predykcji chaotycznych przebiegów czasowych.
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Application of time-series-cross-section data in case of sale forecasting in an enterprise
PublicationW 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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Price bubbles in commodity market – A single time series and panel data analysis
PublicationThis paper examines thirty-five commodities, grouped into three market sectors (energy, metals, agriculture & livestock) in terms of the occurrence of price bubbles. The study was based on monthly data for each commodity separately and, in a panel approach, for selected sectors and for all commodities combined. The GSADF test and its version for panel data – panel GSADF – were used to identify bubbles. The beginning and end of...
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Safety Assessment of the Regional Warmia and Mazury Road Network Using Time-Series Analysis
PublicationWarmia and Mazury still belongs to the areas with the smallest transport accessibility in Europe. Unsatisfactory state of road infrastructure is a major barrier to the development of the regional economy, impacting negatively on the life conditions of the population. Also in terms of road safety Warmia and Mazury is one of the most endangered regions in Poland. The Police statistics show that beside a high pedestrian risk observed...
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Time series of Doppler blood flow recordings
Open Research DataVital signals registration plays a grate role in biomedical engineering and education process. Well acquired data allow future engineers to observe certain physical phenomenons as well learn how to correctly process and interpret the data. This data set was designed for students to learn about Doppler phenomena and to demonstrate correctly and incorrectly...
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Time-series analysis of road safety trends aggregated at national level in Europe for 2000-2010
PublicationThe reader will find in this study road safety modelling theory and time-series analysis techniques, applications to long period data of injury accidents and casualities, aggregared at national level
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Excited state properties of a series of molecular photocatalysts investigated by time dependent density functional theory.
PublicationTime dependent density functional theory calculations are applied on a series of molecular photocatalysts of the type [(tbbpy)2M1(tpphz)M2X2]2+ (M1 = Ru, Os; M2 = Pd, Pt; X = Cl, I) in order to provide information concerning the photochemistry occurring upon excitation of the compounds in the visible region. To this aim, the energies, oscillator strengths and orbital characters of the singlet and triplet excited states are investigated....
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Automatic Cleaning of Time Series Data in Rural Internet of Things Ecosystems That Use Nomadic Gateways
PublicationA serious limitation to the deployment of IoT solutions in rural areas may be the lack of available telecommunications infrastructure enabling the continuous collection of measurement data. A nomadic computing system, using a UAV carrying an on-board gateway, can handle this; it leads, however, to a number of technical challenges. One is the intermittent collection of data from ground sensors governed by weather conditions for...
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Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations
PublicationThe flooding extent area in a river valley is related to river gauge observations such as discharge and water elevations. The higher the water elevations, or discharge, the larger the flooding area. Flooding extent maps are often derived from synthetic aperture radar (SAR) images using thresholding methods. The thresholding methods vary in complexity and number of required parameters. We proposed a simple thresholding method that...
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Testing heart rate asymmetry in long, nonstationary 24 hour RR-interval time series
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Nonlinear Modeling in Time Domain Numerical Analysis of Stringed Instrument Dynamics
PublicationMusical instruments are very various in terms of sound quality with their timbre shaped by materials and geometry. Materials' impact is commonly treated as dominant one by musicians, while it is unclear whether it is true or not. The research proposed in the study focuses on determining influence of both these factors on sound quality based on their impact on harmonic composition. Numerical approach has been chosen to allowed independent...
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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublicationThe GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network...
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Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series
PublicationAdvanced processing of collected global navigation satellite systems (GNSS) observations allows for the estimation of zenith tropospheric delay (ZTD), which in turn can be converted to the integrated water vapour (IWV). The proper estimation of GNSS IWV can be affected by the adopted GNSS processing strategy. To verify which of its elements cause deterioration and which improve the estimated GNSS IWV, we conducted eight reprocessings...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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A Modeling Problem of a Continuous-Time Domain Signal and Its Discrete Counterpart
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Experimental study and mathematical modeling of the residence time distribution in magnetic mixer
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Efficient modeling of the time-domain crosstalk phenomena in coupled microstrip lines
PublicationW pracy przedstawiono efektywną technikę analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych. Analiza uwzględnia hybrydową naturę prowadzonych fal i prowadzi do określenia postaci czasowych sygnałów na zaciskach struktury w zależności od parametrów układu linii sprzężonych oraz własności obciążeń. Wyniki analizy zweryfikowano poprzez porównanie z wynikami badań eksperymentalnych, uzyskując bardzo dobrą zgodność.
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Noise Analysis of Continuous GPS Time Series of Selected EPN Stations to Investigate Variations in Stability of Monument Types
PublicationThe type of monument that a GPS antenna is placed on plays a significant role in noise estimation for each permanent GPS station. In this research 18 Polish permanent GPS stations that belong to the EPN (EUREF Permanent Network) were analyzed using Maximum Likelihood Estimation (MLE). The antennae of Polish EPN stations are placed on roofs of buildings or on concrete pillars. The analyzed data covers a period of 5 years from 2008...
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Investigating the Ischaemic Phase of Skin NADH Fluorescence Dynamics in Recently Diagnosed Primary Hypertension: A Time Series Analysis
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Volterra series usefulness in modelling of the time-domain cross-talk phenomena in coupled microstrip lines with nonlinear termination
PublicationW pracy przedyskutowano możliwość wykorzystania szeregów Volterry do analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych z nieliniowym obciążeniem. Apracowano algorytm metody, zaś uzyskane wyniki numeryczne zweryfikowano poprzez porównania z wynikami badań eksperymentalnych linii obciążonych w torze transmisyjnym diodą Schottky'ego.
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Time Domain Modeling of Propeller Forces due to Ventilation in Static and Dynamic Conditions
PublicationThis paper presents experimental and theoretical studies on the dynamic effect on the propeller loading due to ventilation by using a simulation model that generates a time domain solution for propeller forces in varying operational conditions. For ventilation modeling, the simulation model applies a formula based on the idea that the change in lift coefficient due to ventilation computes the change in the thrust coefficient. It...
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Modeling the effect of parasitic capacitances on the dead-time distortion in multilevel NPC inverters
PublicationA simple model is derived and verified for evaluating the effect of parasitic capacitances on the dead-time related voltage distortion in multilevel NPC voltage source inverters. The model permits well-defined and precise compensation of dead-time distortion, exhibiting meaningful improvement on compensation methods neglecting the effects of parasitic capacitances. A simple formula is given for evaluating the capacitances as serial/parallel...
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Time Domain Modeling of Propeller Forces due to Ventilation in Static and Dynamic Conditions
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Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12
PublicationThis paper presents a review of time-series analysis of road safety trends, aggregatedat a national level, which has been performed in the period 2000 – 12 and applied to Europeannational data sets covering long time periods. It provides a guideline and set of best practices inthe area of time-series modelling and identifies the latest methods and applications of nationalroad safety trend analysis...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis 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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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Time series analysis and impact assessment of the temperature changes on the vegetation and the water availability: A case study of Bakun-Murum Catchment Region in Malaysia
PublicationThe Bakun-Murum (BM) catchment region of the Rajang River Basin (RRB), Sarawak, Malaysia, has been under severe threat for the last few years due to urbanization, global warming, and climate change. The present study aimed to evaluate the time series analysis and impact assessment of the temperature changes on the vegetation/agricultural lands and the water availability within the BM region. For this purpose, the Landsat data for...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment
PublicationArtykuł prezentuje kompletne rozwiązanie do modelowania naukowych i biznesowych scenariuszy. statycznego i dynamicznego wyboru usług z uwzględnieniem parametrów jakościowych oraz wykonanie scenariuszy w rzeczywistym środowisku. Scenariusz jest modelowany jako acykliczny graf skierowany, w którym węzły reprezentują zadania zaś krawędzie zależności pomiędzy zadaniami. Warstwa pośrednia BeesyCluster jest wykorzystana do umożliwienia...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...