Fawaz E. Alsaadi

TL;DR: An experimental study is designed to compare five MCDM methods to validate the proposed approach with 10 feature selection methods, nine evaluation measures for binary classification, seven Evaluation measures for multi-class classification, and three classifiers with 10 small datasets, and the results demonstrate the effectiveness of the used M CDM-based method in evaluating feature selection method.

TL;DR: This paper surveys existing researches and methodologies on assessment and measurement of financial systemic risk combined with machine learning technologies, including big data analysis, network analysis and sentiment analysis, etc.

TL;DR: The stability of the closed-loop system is proven via a fractional version of the Lyapunov stability theorem and Barbalat's lemma and the developed control technique on the uncertain fractional-order hyperchaotic memristor oscillator is investigated.

TL;DR: The fusion estimation problem is studied for a class of discrete time-varying multi-rate linear repetitive processes (LRPs) under weighted try-once-discard protocol, and a set of local estimators is designed such that the upper bounds on the local estimation error covariances are guaranteed.

TL;DR: Numerical results demonstrate the chattering-free and effective performance of the proposed control method for uncertain systems in the presence of unknown time-varying external disturbances.