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Wyniki wyszukiwania dla: TIME SERIES
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TIME SERIES MODELING (PG_00063724)
Kursy OnlineEffectively 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
Kursy Onlineprowadzący: assoc. prof. Ján Dvorský, PhD
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Investigation of noises in the EPN weekly time series
PublikacjaThe 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
PublikacjaThanks 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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Time series - the tool for traffic safety analysis
PublikacjaGłównym 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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Short-Period Information in GPS Time Series
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Traffic fatalities modelling using time-series.
PublikacjaReferat 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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Traffic risk modelling using time-series
PublikacjaW 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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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
PublikacjaTime 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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Road safety analysis in Poland using time-series modelling techniques
PublikacjaA 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
PublikacjaThe 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).
PublikacjaPrzedstawiono 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
PublikacjaOne 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
PublikacjaPrzedstawiono 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
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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Price bubbles in commodity market – A single time series and panel data analysis
PublikacjaThis 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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Time series of Doppler blood flow recordings
Dane BadawczeVital 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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Safety Assessment of the Regional Warmia and Mazury Road Network Using Time-Series Analysis
PublikacjaWarmia 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 analysis of road safety trends aggregated at national level in Europe for 2000-2010
PublikacjaThe 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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Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations
PublikacjaThe 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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric 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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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublikacjaThe 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
PublikacjaAdvanced 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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Noise Analysis of Continuous GPS Time Series of Selected EPN Stations to Investigate Variations in Stability of Monument Types
PublikacjaThe 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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Road Safety Trends at National Level in Europe: A Review of Time-series Analysis Performed during the Period 2000–12
PublikacjaThis 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
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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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
PublikacjaThe 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
PublikacjaAir 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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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir 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...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Excited state properties of a series of molecular photocatalysts investigated by time dependent density functional theory.
PublikacjaTime 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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Zastosowanie analizy szeregów czasowych do oceny zanieczyszczenia powietrza atmosferycznego w rejonie Trójmiasta. Application of time series analysis on air quality assessment in the region of Tricity
PublikacjaNa podstawie analizy wyników pomiarów poziomów stężenia: NO3-, SO42-, F- ,Cl-, NH4+, PO43-, Ca2+, K+, Mg2+ oraz pomiarów pH i przewodności elektrolitycznej próbek wód opadowych na terenie Trójmiasta z zastosowaniem techniki analizy szeregów czasowych wykazano, że cykliczne wahania poziomów depozycji SO42-, F-, NO3- i Ca2+ w próbkach są skorelowane z cyklicznymi 9 zmianami przeważających kierunków wiatrów. Analiza struktury szeregów...
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Volterra series usefulness in modelling of the time-domain cross-talk phenomena in coupled microstrip lines with nonlinear termination
PublikacjaW 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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Hourly GNSS-derived integrated moisture in the global tropics for the years 2001-2018
Dane BadawczeGlobal tropics are essential in formulating weather patterns and climate across various latitudes through atmospheric teleconnections. Since water vapour is an essential parameter in atmospheric convection and, thus, latent heat release, its tropical variability on different time scales is crucial in understanding weather and climate changes. The provided...
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Tropospheric parameters derived from the selected IGS stations in the global tropics for the years 2001-2018
Dane BadawczeThis dataset contains daily GNSS-derived zenith tropospheric delay (ZTD), a posteriori corrected zenith wet delay (ZWD), and precipitable water vapour (PWV) time series. These troposphere-related data were estimated for the period between January 2001 and December 2018, for the 43 International GNSS Service (IGS) stations, located in the global tropics....
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Olgun Aydin dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Statistical Method for Analysis of Interactions Between Chosen Protein and Chondroitin Sulfate in an Aqueous Environment
PublikacjaWe present the statistical method to study the interaction between a chosen protein and another molecule (e.g., both being components of lubricin found in synovial fluid) in a water environment. The research is performed on the example of univariate time series of chosen features of the dynamics of mucin, which interact with chondroitin sulfate (4 and 6) in four different saline solutions. Our statistical approach is based on recurrence...
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Floodsar: Automatic mapping of river flooding extent from multitemporal SAR imagery
PublikacjaFloodsar is an open-source tool for automatic mapping of the flood extent from a time series of synthetic aperture radar (SAR) imagery. Floodsar is unsupervised, however, it requires defining the parameters search space, geographical area of interest, and some river gauge observations (e.g. water levels or discharges) time series that overlap temporarily with the SAR imagery. Applications of Floodsar are mainly in real-time monitoring...
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Investigation of long-range dependencies in the stochastic part of daily GPS solutions
PublikacjaThe long-range dependence (LRD) of the stochastic part of GPS-derived topocentric coordinates change (North, East, Up) results with relatively high autocorrelation values with a focus on self-similarity. One of the reasons for such self-similarity in the GPS time series are noises that are commonly recognised to prevail in the form of the flicker noise model. To prove the self-similarity of the stochastic part of GPS time series...
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Application of MARKAL model to optimisation of electricity generation structure in Poland in the long-term time horizon Part I - concept of the model
PublikacjaIn this paper, which inaugurates a series of papers on this subject, a concept is proposed of a power system development model with regard to the technological structure of electricity generation in Poland, in the long-term time perspective – until 2060. The model is based on the mathematical structure of the MARKAL optimization package. The paper presents a brief description of the tool used in the model research. In addition,...
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Porous Phantoms Mimicking Tissues—Investigation of Optical Parameters Stability Over Time
PublikacjaOptical phantoms are used to validate optical measurement methods. The stability of their optical parameters over time allows them to be used and stored over long-term periods, while maintaining their optical parameters. The aim of the presented research was to investigate the stability of fabricated porous phantoms, which can be used as a lung phantom in optical system. Measurements were performed in multiple series with an interval...
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Long-Term GNSS Tropospheric Parameters for the Tropics (2001-2018) Derived from Selected IGS Stations
PublikacjaThis paper describes dataset “Tropospheric parameters derived from selected IGS stations in the tropics for the years 2001-2018” contains GNSS-derived zenith tropospheric delay (ZTD), a posteriori corrected zenith wet delay (ZWD), and precipitable water vapour (PWV) time series. These troposphere-related data were estimated for the Jan 2001 – Dec 2018 period for 43 International GNSS Service (IGS) stations located across the global...
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Studies of the Interaction Dynamics in Albumin-Chondroitin Sulfate Systems by Recurrence Method
PublikacjaThe physicochemical basis of lubrication of articular cartilage is still not fully understood. However, the synergy between components of the synovial fluid can be a crucial factor that could explain this phenomenon. This work presents a nonlinear data analysis technique named the recurrence method, applied to the system involving two components of synovial fluid: albumin and chondroitin sulfate (CS) immersed in a water environment....
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Analytical solution of non-stationary heat conduction problem for two sliding layers with time-dependent friction conditions
PublikacjaIn this article we conduct an overview of various types of thermal contact conditions at the sliding interface. We formulate a problem of non-stationary heat conduction in two sliding layers with generalized thermal contact conditions allowing for dependence of the heat-generation coefficient and contact heat transfer coefficient on time. We then derive an analytical solution of the problem by constructing a special coordinate...