Search results for " time-series"
showing 10 items of 15 documents
Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system
2014
Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…
Comparison of discretization strategies for the model-free information-theoretic assessment of short-term physiological interactions
2023
This work presents a comparison between different approaches for the model-free estimation of information-theoretic measures of the dynamic coupling between short realizations of random processes. The measures considered are the mutual information rate (MIR) between two random processes [Formula: see text] and [Formula: see text] and the terms of its decomposition evidencing either the individual entropy rates of [Formula: see text] and [Formula: see text] and their joint entropy rate, or the transfer entropies from [Formula: see text] to [Formula: see text] and from [Formula: see text] to [Formula: see text] and the instantaneous information shared by [Formula: see text] and [Formula: see…
The Euro-Dollar Exchange Rate: Is it Fundamental?
2002
In this paper we have applied two approaches to the study of the dollar real exchange rate in relation with the Euro-area currencies. First, using dynamic panel techniques, we estimate an error correction model for the dollar real exchange rate versus seven developed countries, four of them Euro-area members. Second, we aggregate the European variables and estimate a model for the Euro-dollar real exchange rate using time series techniques. After identification and model selection, the same specification can be adopted in the two cases, in an eclectic model including real interest rate and productivity differentials, together with relative fiscal policy and net foreign asset positions. This…
Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market
2010
What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stoc…
An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension
2020
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying the experimental setup and in employing an easier to use data processing procedure for the acquired time-series. A DLS time series processing procedure based on an artificial neural network is presented with details regarding the design, training procedure and error analysis, working over an extended particle size range. The procedure proved to be much faster regarding time-series processing and easier to use than fitti…
High-to-low (Regional) fertility transitions in a peripheral european country: The contribution of exploratory time series analysis
2021
Diachronic variations in demographic rates have frequently reflected social transformations and a (more or less evident) impact of sequential economic downturns. By assessing changes over time in Total Fertility Rate (TFR) at the regional scale in Italy, our study investigates the long-term transition (1952–2019) characteristic of Mediterranean fertility, showing a continuous decline of births since the late 1970s and marked disparities between high- and low-fertility regions along the latitude gradient. Together with a rapid decline in the country TFR, the spatiotemporal evolution of regional fertility in Italy—illustrated through an exploratory time series statistical approach—outlines th…
Long-Term Hydrological Regime Monitoring of a Mediterranean Agro-Ecological Wetland Using Landsat Imagery: Correlation with the Water Renewal Rate of…
2021
The Natural Park of Albufera (Valencia, Spain) is one of the Spanish Mediterranean wetlands where rice is cultivated intensively. The hydrology of the Albufera Lake, located in the center, combines natural contributions with complex human management. The aim of our study was to develop a new methodology to accurately detect the volume of flood water in complex natural environments which experience significant seasonal changes due to climate and agriculture. The study included 132 Landsat images, covering a 15-year period. The algorithm was adjusted using the NDWI index and simultaneous measurements of water levels in the rice fields. The NDVI index was applied to monitor the cultivated area…
Information decomposition in the frequency domain: a new framework to study cardiovascular and cardiorespiratory oscillations
2021
While cross-spectral and information-theoretic approaches are widely used for the multivariate analysis of physiological time series, their combined utilization is far less developed in the literature. This study introduces a framework for the spectral decomposition of multivariate information measures, which provides frequency-specific quantifications of the information shared between a target and two source time series and of its expansion into amounts related to how the sources contribute to the target dynamics with unique, redundant and synergistic information. The framework is illustrated in simulations of linearly interacting stochastic processes, showing how it allows us to retrieve …
Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles
2022
Synthetic aperture radar (SAR) data provides an appealing opportunity for all-weather day or night Earth surface monitoring. The European constellation Sentinel-1 (S1) consisting of S1-A and S1-B satellites offers a suitable revisit time and spatial resolution for the observation of croplands from space. The C-band radar backscatter is sensitive to vegetation structure changes and phenology as well as soil moisture and roughness. It also varies depending on the local incidence angle (LIA) of the SAR acquisition’s geometry. The LIA backscatter dependency could therefore be exploited to improve the retrieval of the crop biophysical variables. The availability of S1 radar time-series data at d…
Monitoring the invasion of an exotic tree (Ailanthus altissima) (Mill.) Swingle with Landsat satellite time series imagery in urban forest.
2015
In the Mediterranean area, one the most threat tree to various ecosystems is Ailanthus altissima (Mill.) Swingle. This is an aggressive invasive species common in natural and semi-natural habitat. Monitoring and mapping of invasive species is an important information for the conservation and management of ecosystems. The study of distribution and diffusion of invasive species are useful to assess their environmental impacts, formulate effective control strategies, and forecast potential spread. The main target of this work is to examine the feasibility of mapping the expansion of A. altissima using remote sensing techniques in a highly complex urban forest setting. Remote sensing has been a…