The neural network technique - 1: a general exposition

Tulunay, Yurdanur
Tulunay, E
Senalp, ET
Near earth space processes are highly complex and nonlinear and mathematical modeling based on first physical principals is usually difficult or impossible. For such cases data driven modeling methods are recommended to be used in parallel with mathematical modeling approach. Highly non-linear processes in the near-earth space are advantageously dealt with using data-driven modeling techniques in the neural network (NN) approach. The only basic requirement for its application is the availability of representative data. (C) 2003 COSPAR. Published by Elsevier Ltd. All rights reserved.


Forecasting magnetopause crossing locations by using Neural Networks
Tulunay, Yurdanur; Sibeck, DG; Senalp, ET; Tulunay, E (Elsevier BV, 2005-01-01)
Given the highly complex and nonlinear nature of Near Earth Space processes, mathematical modeling of these processes is usually difficult or impossible. In such cases, modeling methods involving Artificial Intelligence may be employed. We demonstrate that data driven models, such as the Neural Network based approach, shows promise in its ability to forecast or predict the behavior of these processes. In this paper, modeling studies for forecasting magnetopause crossing locations are summarized and a Neural...
The neural network technique - 2: an ionospheric example illustrating its application
Tulunay, Yurdanur; Tulunay, E; Senalp, ET (Elsevier BV, 2004-01-01)
An example of modeling of Near Earth Space Processes by empoying the Neural Network Approach [Tulunay et al., Adv. Space Res., this current issue, 2003] is considered. The temporal and spatial forecasting of ionospheric critical frequency f(o)F2 values up to 24 h in advance by using the METUNN model is briefly covered. (C) 2003 COSPAR. Published by Elsevier Ltd. All rights reserved.
Regional VTEC modeling with multivariate adaptive regression splines
Durmaz, Murat; Karslıoğlu, Mahmut Onur; Nohutcu, Metin (Elsevier BV, 2010-07-15)
Different algorithms have been proposed for the modeling of the ionosphere. The most frequently used method is based on the spherical harmonic functions achieving successful results for global modeling but not for the local and regional applications due to the bounded spherical harmonic representation. Irregular data distribution and data gaps cause also difficulties in the global modeling of the ionosphere. In this paper we propose an efficient algorithm with Multivariate Adaptive Regression Splines (MARS)...
The momentum 4-vector imparted by gravitational waves in Bianchi-type metrics
Havare, A; Korunur, M; Salti, M (Springer Science and Business Media LLC, 2006-01-01)
Considering the MOller, Weinberg and Qadir-Sharif's definitions in general relativity, we find the momentum 4-vector of the closed universe based on the Bianchi-type metrics. The momentum 4-vector (due to matter plus fields) is found to be zero. This result supports the viewpoints of Albrow and Tryon and extends the previous works by Cooperstock-Israelit, Rosen, Johri et al., Banerjee-Sen and Vargas who investigated the problem of the energy in Friedmann-Robertson-Walker universe and SaltI-Havare who studie...
BAYIN, SS; COOPERSTOCK, FI; FARAONI, V (American Astronomical Society, 1994-06-20)
We explore the possibility of describing our universe with a singularity-free, closed, spatially homogeneous and isotropic cosmological model, using only general relativity and a suitable equation of state which produces an inflationary era. A phase transition to a radiation-dominated era occurs as a consequence of boundary conditions expressing the assumption that the temperature cannot exceed the Planck value. We find that over a broad range of initial conditions, the predicted value of the Hubble paramet...
Citation Formats
Y. Tulunay, E. Tulunay, and E. Senalp, “The neural network technique - 1: a general exposition,” PATH TOWARD IMPROVED IONOSPHERE SPECIFICATION AND FORECAST MODELS, pp. 983–987, 2004, Accessed: 00, 2020. [Online]. Available: