Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

Abstract

In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

Community detection analysis in wind speed-monitoring systems using mutual information-based complex network

“…15,35 The topological properties of wind systems have been a focus of investigation only in the very recent years. Laib et al 23 studied the long-range uctuations in the connectivity density time series of a correlation-based network of high-dimensional wind speed time series recorded by a monitoring system in Switzerland. They found that the daily time series of a connectivity density of the wind speed network is characterized by a clear annual periodicity that modulates the connectivity density more intensively for low than high absolute values of the correlation threshold.…”

Application of GM (1,1) and Seasonal Cross-Trend Model in the Forecast of Tourist Population in Sanya

“…GraymodelGM(1,1)canbeusedasashort-termforecastwithhighaccuracywhen theoriginalsequenceimpliedexponentialchanges.Theseasonalcross-multiplicationtrendmodel isakindoftimeseriesmodel[Analysisoftrend,periodicities,andcorrelationsintheberyllium-7 timeseriesinNorthernEurope (Bianchi,2019,p.160)]. Ifthefluctuationofthesequencehasboth trendandseasonalinfluence,andthetrendrisesorfallsatasteadyrate.Theseasonalinfluenceis thesameasthatshownintheseasonalhorizontaltimeseriesmodel,anditsseasonalfluctuationis largerwhenthelevelofthetrendpartishigherthanthatofthelowlevel,whichisverysuitablefor theforecastusingtheseasonalcrossproducttrendmodel[Periodicfluctuationsincorrelation-based connectivitydensitytimeseries:Applicationtowindspeed-monitoringnetworkinSwitzerland (Laib, 2018(Laib, ,p.1555]. Theseasonalmutualtendencymodelhasbeenappliedineconomyandelectricpower.…”