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Oppositional Biogeography-Based Optimization, Mehmet Ergezer
Oppositional Biogeography-Based Optimization, Mehmet Ergezer
ETD Archive
This dissertation outlines a novel variation of biogeography-based optimization (BBO), which is an evolutionary algorithm (EA) developed for global optimization. The new algorithm employs opposition-based learning (OBL) alongside BBO migration to create oppositional BBO (OB BO). Additionally, a new opposition method named quasi-reflection is introduced. Quasireflection is based on opposite numbers theory and we mathematically prove that it has the highest expected probability of being closer to the problem solution among all OBL methods that we explore. Performance of quasi-opposition is validated by mathematical analysis for a single-dimensional problem and by simulations for higher dimensions. Experiments are performed on benchmark …
Evolutionary Optimization Of Atrial Fibrillation Diagnostic Algorithms, Aref Smiley
Evolutionary Optimization Of Atrial Fibrillation Diagnostic Algorithms, Aref Smiley
ETD Archive
The goal of this research is to introduce an improved method for detecting atrial fibrillation (AF). The foundation of our algorithm is the irregularity of the RR intervals in the electrocardiogram (ECG) signal, and their correlation with AF. Three statistical techniques, including root mean squares of successive differences (RMSSD), turning points ratio (TPR), and Shannon entropy (SE), are used to detect RR interval irregularity. We use the Massachusetts Institution of Technology / Beth Israel Hospital (MIT-BIH) atrial fibrillation databases and their annotations to tune the parameters of the statistical methods by biogeography-based optimization (BBO), which is an evolutionary optimization algorithm. …