Using intelligent optimization methods to improve the group method of data handling in time series prediction

In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The new improved GMDH is then used to predict currency exchange rates: the US Dollar to the Euros. The performance of the hybrid GMDHs are compared with that of the conventional GMDH. Two performance measures, the root mean squared error and the mean absolute percentage errors show that the hybrid GMDH algorithm gives more accurate predictions than the conventional GMDH algorithm

Modelling and Prediction of Global Magnetic Disturbance in Near-Earth Space: a Case Study for Kp Index using NARX Models

Severe geomagnetic disturbances can be hazardous for mod-ern technological systems. The reliable forecast of parameters related to thestate of the magnetosphere can facilitate the mitigation of adverse effects ofspace weather. This study is devoted to the modeling and forecasting of theevolution of the Kp index related to global geomagnetic disturbances. Through-out this work the Nonlinear AutoRegressive with eXogenous inputs (NARX)methodology is applied. Two approaches are presented: i) a recursive slid-ing window approach, and ii) a direct approach. These two approaches arestudied separately and are then compared to evaluate their performances.It is shown that the direct approach outperforms the recursive approach, butboth tend to produce predictions slightly biased from the true values for lowand high disturbances

A novel logistic-NARX model as a classifier for dynamic binary classification

System identification and data-driven modeling techniques have seen ubiquitous applications in the past decades. In particular, parametric modeling methodologies such as linear and nonlinear autoregressive with exogenous input models (ARX and NARX) and other similar and related model types have been preferably applied to handle diverse data-driven modeling problems due to their easy-to-compute linear-in-the-parameter structure, which allows the resultant models to be easily interpreted. In recent years, several variations of the NARX methodology have been proposed that improve the performance of the original algorithm. Nevertheless, in most cases, NARX models are applied to regression problems where all output variables involve continuous or discrete-time sequences sampled from a continuous process, and little attention has been paid to classification problems where the output signal is a binary sequence. Therefore, we developed a novel classification algorithm that combines the NARX methodology with logistic regression and the proposed method is referred to as logistic-NARX model. Such a combination is advantageous since the NARX methodology helps to deal with the multicollinearity problem while the logistic regression produces a model that predicts categorical outcomes. Furthermore, the NARX approach allows for the inclusion of lagged terms and interactions between them in a straight forward manner resulting in interpretable models where users can identify which input variables play an important role individually and/or interactively in the classification process, something that is not achievable using other classification techniques like random forests, support vector machines, and k-nearest neighbors. The efficiency of the proposed method is tested with five case studies

Moderate drinking before the unit: medicine and life assurance in Britain and the US c.1860–1930

This article describes the way in which “Anstie’s Limit” – a particular definition of moderate drinking first defined in Britain in the 1860s by the physician Francis Edmund Anstie (1833–1874) – became established as a useful measure of moderate alcohol consumption. Becoming fairly well-established in mainstream Anglophone medicine by 1900, it was also communicated to the public in Britain, North America and New Zealand through newspaper reports. However, the limit also travelled to less familiar places, including life assurance offices, where a number of different strategies for separating moderate from excessive drinkers emerged from the dialogue between medicine and life assurance. Whilst these ideas of moderation seem to have disappeared into the background for much of the twentieth century, re-emerging as the “J-shaped” curve, these early developments anticipate many of the questions surrounding uses of the “unit” to quantify moderate alcohol consumption in Britain today. The article will therefore conclude by exploring some of the lessons of this story for contemporary discussions of moderation, suggesting that we should pay more attention to whether these metrics work, where they work and why

The Physical Processes of CME/ICME Evolution

As observed in Thomson-scattered white light, coronal mass ejections (CMEs) are manifest as large-scale expulsions of plasma magnetically driven from the corona in the most energetic eruptions from the Sun. It remains a tantalizing mystery as to how these erupting magnetic fields evolve to form the complex structures we observe in the solar wind at Earth. Here, we strive to provide a fresh perspective on the post-eruption and interplanetary evolution of CMEs, focusing on the physical processes that define the many complex interactions of the ejected plasma with its surroundings as it departs the corona and propagates through the heliosphere. We summarize the ways CMEs and their interplanetary CMEs (ICMEs) are rotated, reconfigured, deformed, deflected, decelerated and disguised during their journey through the solar wind. This study then leads to consideration of how structures originating in coronal eruptions can be connected to their far removed interplanetary counterparts. Given that ICMEs are the drivers of most geomagnetic storms (and the sole driver of extreme storms), this work provides a guide to the processes that must be considered in making space weather forecasts from remote observations of the corona.Peer reviewe

Evidence-Based Guidelines on Health Promotion for Older People

The central aim of the healthPROelderly project was to contribute fundamentally to the development of health promotion for older people through producing guidelines and recommendations for potential actors in this field at EU, national and local level. The specific objectives of the healthPROelderly project were: ? to carry out a literature review concerning health promotion of older people in each of the participating countries. ? to identify models for health promotion for older people in each of the participating countries, evaluate three of them in each country and make them available in the form of a database on the website (www.healthproelderly.com). ? to inform and raise the awareness among experts and authorities throughout the EU about the issue of ageing and the impact of demographic change on our society