Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

A comparison of methods to avoid overfitting in neural networks training in the case of catchment runoff modelling

A statistical point-process model is derived to describe the standard activity of earthquake occurrences by assuming that general seismicity is given by the superposition of aftershock sequences. The parameters are estimated ty the maximum likelihood method. Using the estimated model, the “residual point process” of the data is defined and used to find the anomalies which are included in the data set but not captured in the considered model for the standard seismicity. For instance, seismic quiescences can be measured quantitatively by using the residual process. Some examples are provided to illustrate such analyses. Furthermore, a time series of the magnitudes on the residual point process is considered, to investigate its dependence either on the time or on the history of the seismicity. By assuming the exponential distribution at each time and modelling of the b- value , we can examine such dependences and estimate them. Two practical examples are shown.

Statistical model for standard seismicity and detection of anomalies by residual analysis

Optimizing neural networks for river flow forecasting – Evolutionary Computation methods versus the Levenberg–Marquardt approach

Lightning produces electromagnetic fields and waves in all frequency ranges. In the extremely low frequency (ELF) range below 100 Hz, the global Schumann Resonances (SR) are excited at frequencies of 8 Hz, 14 Hz, 20 Hz, etc. This review is aimed at the reader generally unfamiliar with the Schumann Resonances. First some historical context to SR research is given, followed by some theoretical background and examples of the extensive use of Schumann resonances in a variety of lightning-related studies in recent years, ranging from estimates of the spatial and temporal variations in global lighting activity, connections to global climate change, transient luminous events and extraterrestrial lightning. Both theoretical and experimental results of the global resonance phenomenon are presented. It is our hope that this review will increase the interest in SR among researchers previously unfamiliar with this phenomenon.

https://www.mdpi.com/2073-4433/7/9/116/pdf

ELF Electromagnetic Waves from Lightning: The Schumann Resonances

Coupled equations are derived for different ionospheric parameters through susceptibility dyadic appropriate to the medium. The nature of dispersion within the medium is studied.

Derivations of coupled equations appropriate to the lower regions of the ionosphere

Field intensities within the ionospheric medium during nonlinear transient processes due to interactions among different modes of propagation have been derived taking into consideration the influence of geomagnetic field. The expression for angular distribution of power during wave propagation has also been evaluated.

Interaction within the Ionosphere in the Presence of Geomagnetic Field

Electromagnetic fields due to earthquake have been studied in this presentation through some model calculations. The expressions of the variation of electron concentration and electron temperature as the ionospheric precursors of earthquake have been deduced in this presentation through quasihydrodynamic formulations. The outcome of the analyses of electromagnetic emissions recorded by VLF receivers at 5, 7, 9 and 12 kHz on November 16, 2008 over Kolkata (Lat. 22.56° N, Long. 88.5° E) during the large earthquake at Minahasa, Sulawesi (Lat. 1.27° N, Long. 122.09° E), under Indonesia have been presented here. Spiky variations of signals are observed few days prior to the day of occurrence of the earthquake which continued several days more, then decayed gradually and eventually ceased.

Syam Sundar De

Papers

Derivations of coupled equations appropriate to the lower regions of the ionosphere

Interaction within the Ionosphere in the Presence of Geomagnetic Field

On some effects of perturbations in the ionosphere due to electromagnetic precursory signals from earthquake