Parcourir par sujet "Time series analysis"
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Application of deep learning and chaos theory for load forecasting in Greece
(2021)In this paper, a novel combination of deep learning recurrent neural network and Lyapunov time is proposed to forecast the consumption of electricity load, in Greece, in normal/abrupt change value areas. Our method verifies ... -
Atlantes: Automated Health Related & COVID-19 Data Management for Use in Predictive Models
(2022)The scientific community, having turned its interest, almost entirely, to the treatment and understanding of COVID-19, is constantly striving to collect and use data from the countless available sources. That data, however, ... -
Backward Degree a new index for online and offline change point detection based on complex network analysis
(2022)How to identify an upcoming transition in a time series continues to be an important open research issue. In various fields of physical sciences, engineering, finance and neuroscience abrupt changes can occur unexpectedly ... -
Can reconstructed land surface temperature data from space predict a West Nile Virus outbreak?
(2017)Temperature is one of the main drivers of ecological processes. The availability of temporally and spatially continuous temperature time series is crucial in different research and application fields, such as epidemiology ... -
Capturing system dynamics using complex networks and granger causality analysis: Application to environmental data
(2016)In the present study, we introduce a novel methodology to analyze environmental observations. Environmental phenomena are usually complex and the majority of them present nonlinear behavior. In the first part of the present ... -
A comparative analysis of performances of econometric, fuzzy and time-series models for the forecast of transport demand
(2007)The paper attempts to evaluate how the fuzzy method can improve the range of forecast achieved by classic econometric and time-series models. Based on a survey of factors affecting rail passenger demand and using data of ... -
Comparative Energy Information Analytics of Five European Economies
(2020)Real GDP per capita and energy consumption are often, but not always, correlated variables. Comparative analysis of their respective time series offers new insights and information and new decision-making metrics. During ... -
Detection of jet axis in a horizontal turbulent jet via nonlinear analysis of minimum/maximum temperature time series
(2019)We have analyzed experimental temperature time series from a horizontal turbulent heated jet, in order to identify the jet axis location using non linear measures. The analysis was applied on both, the original time series ... -
Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis
(2018)Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly ... -
Evaluation of Water Resources Management Strategies to Overturn Climate Change Impacts on Lake Karla Watershed
(2016)The effects of climate change on meteorology, hydrology and ecology have become a priority area for research and for water management. It is crucial to identify, simulate, evaluate and, finally, adopt water resources ... -
Exploiting the Knowledge of Dynamics, Correlations and Causalities in the Performance of Different Road Paths for Enhancing Urban Transport Management
(2019)The great abundance of multi-sensor traffic data (traditional traffic data sources - loops, cameras and radars accompanied or even replaced by the most recent - Bluetooth detectors, GPS enabled floating car data) although ... -
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in Greece
(2019)This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim ... -
Load curves partitioning with the application of soft clustering algorithms
(2019)Load profiling refers to a procedure which leads to the formulation of daily load curve and consumer categories regarding the similarity of their curves shapes. This procedure incorporates a set of pattern recognition ... -
Modelling cyber-risk in an economic perspective
(2021)In this paper, we present a theoretical approach concerning the econometric modelling for the estimation of cyber-security risk, with the use of time-series analysis methods and alternatively with Machine Learning (ML) ... -
Pattern identification for wind power forecasting via complex network and recurrence plot time series analysis
(2019)Renewable energy sources, where wind energy is an important part, are increasingly participating in developing economies and environmental benefits. Wind power is strongly dependent on wind velocity and thus identifying ... -
Recurrence quantification analysis of MHD turbulent channel flow
(2019)We present Recurrence Plots (RPs) and Recurrence Quantification Analysis (RQA) of time series of velocities in a low-Reynolds-number magnetohydrodynamic turbulent channel flow. The flow was simulated using a fully spectral ... -
RNNs for Classification of Driving Behaviour
(2019)Recurrent neural networks are an obvious choice for driving behavior analysis by means of time series of measurements, obtained either from telematics or mobile phone sensors. This work investigates such an application, ... -
Role of microbial diversity for sustainable pyrite oxidation control in acid and metalliferous drainage prevention
(2020)Acid and metalliferous drainage (AMD) remains a challenging issue for the mining sector. AMD management strategies have attempted to shift from treatment of acid leachates post-generation to more sustainable at-source ... -
Spatiotemporal Time Series Analysis Methods for the Study of Turbulent Magnetohydrodynamic Channel Flows
(2015)In the present study, the direct numerical simulation of the turbulent flow of an electrically conductive fluid in a channel is performed and time series are recorded at a range of locations along the y-direction between ... -
Text Analysis of COVID-19 Tweets
(2022)During the COVID-19 pandemic many countries were forced to implement lockdowns to prevent further spread of the SARS-CoV-2, prohibiting people from face-to-face social interactions. This unprecedented circumstance led to ...