A machine learning-based electron density (MLED) model in the inner magnetosphere

Equatorial electron density measurements in Saturn’s inner magnetosphere

Electron density in the magnetosphere

[1] Observations of the electron density ne based on measurement of the upper hybrid resonance frequency by the Polar spacecraft Plasma Wave Instrument (PWI) are available for March 1996 to September 1997, during which time the Polar orbit sampled all MLT values three times. In a previous study, we modeled the electron density dependence along field lines as ne = ne0(Rmax/R) , where ne0 is the ...

Emotion Detection in Persian Text; A Machine Learning Model

This study aimed to develop a computational model for recognition of emotion in Persian text as a supervised machine learning problem. We considered Pluthchik emotion model as supervised learning criteria and Support Vector Machine (SVM) as baseline classifier. We also used NRC lexicon and contextual features as training data and components of the model. One hundred selected texts including pol...

A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements

Financial statement fraud has increasingly become a serious problem for business, government, and investors. In fact, this threatens the reliability of capital markets, corporate heads, and even the audit profession. Auditors in particular face their apparent inability to detect large-scale fraud, and there are various ways to identify this problem. In order to identify this problem, the majori...

Model-based machine learning

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations....