International Journal of Scientific Engineering and Technology

N. Gururajan ¹, V. Kayalvizhi Prabhakaran ¹

Affiliations
1 Kanchi Mamunivar Centre for Post Graduate Studies, Pondicherry-8, IN

Abstract

Poincare plot is a nonlinear method. It is a graphical representation of the correlation between consecutive RR intervals. It is a graph where each RR interval is plotted against the next RR interval. It is an emerging quantitative visual technique, where, the shape of the plot is categorized into functional classes. The inter-relationships of the geomagnetic components D (declination ), H (horizontal ), Z ( downward ) at four Indian geomagnetic observatories Alibag (ALB), Hyderabad (HYD), Pondicherry (PON), and Visakhapatnam (VIZ) from January 1995 to December 1997 is determined. Towards this purpose, the places which have certain common characteristics are analyzed using Poincare plot analysis.

Keywords

Poincare Plot, Standard Deviation, RR Intervals, Geomagnetic Components, Monthly Sq Variation.

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N. Gururajan ¹, V. Kayalvizhi Prabhakaran ¹

Affiliations
1 Dept. of Mathematics, Kanchi Mamunivar Centre for Post Graduate Studies, Pondicherry-8, IN

Abstract

Considering the three components of the geomagnetic field as stochastic quantities, we used neural networks to study their time evolution in years. In order to find the best NN for the time predictions, we tested different kinds of NN and different ways of their training, where the inputs and targets are long hourly time series of geomagnetic field values. The found NN was used to predict the values of the hourly mean values of the geomagnetic field components.

Keywords

Geomagnetic Field, Geomagnetic Components, Neural Networks (NN), Time Series, Time Prediction.

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