Geomagnetic Activity Characterized by the K Indices
نویسندگان
چکیده
منابع مشابه
Quasi-biennial and quasi-triennial oscillations in geomagnetic activity indices
Data for geomagnetic activity index aa for 1868±1994 were subjected to spectral analysis for 12 intervals each of 11 consecutive years. In each interval, QBO and QTO (quasi-biennial and quasi-triennial oscillations) were observed at 2:00, 2.15, 2.40, 2.70 y and 3:20, 3.40 y, but not all in all intervals. These ̄uctuations are absent near (2±3 y before and after) the sunspot minima and are presen...
متن کاملregular ag-groupoids characterized by ( , ) k q -fuzzy ideals
in this paper, we introduce a considerable machinery which permits us to characterize a number of special (fuzzy) subsets in ag -groupoids. generalizing the concepts of (,q) -fuzzy bi-ideals (interior ideal), we define ( , ) k q -fuzzy bi-ideals, ( , ) k q -fuzzy left (right)-ideals and ( , ) k q -fuzzy interior ideals in ag -groupoids and discuss some fundamental aspects of these i...
متن کاملOn the periodic variations of geomagnetic activity indices Ap and ap
Yearly averages of geomagnetic activity indices Ap for the years 1967±1984 are compared to the respective averages of m Bs, where v is the solar wind velocity and Bs is the southward interplanetary magnetic ®eld (IMF) component. The correlation of both quantities is known to be rather good. Comparing the averages of Ap with m and Bs separately we ®nd that, during the declining phase of the sola...
متن کاملModelling Geomagnetic Activity Data
Strong geomagnetic activity is a hazard to electronics and electric power facilities. Assessment of the actual geomagnetic activity level from local magnetometer monitoring therefore is of importance for risk assessment but also in earth sciences and exploration. Wavelet based signal processing methods are applied to extract meaningful information from magnetic field time series in a noisy envi...
متن کاملAdaptive brain emotional decayed learning for online prediction of geomagnetic activity indices
In this paper we propose adaptive brain-inspired emotional decayed learning to predict Kp, AE and Dst indices that characterize the chaotic activity of the earth's magnetosphere by their extreme lows and highs. In mammalian brain, the limbic system processes emotional stimulus and consists of two main components: Amygdala and Orbitofrontal Cortex (OFC). Here, we propose a learning algorithm for...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of geomagnetism and geoelectricity
سال: 1950
ISSN: 0022-1392
DOI: 10.5636/jgg.2.86