Title: Multi-objektive evolution�re Algorithmen f�r neuronale Spitzennetze (German Edition)
Publisher: Verlag Unser Wissen
Publication Date: 2025
Language: German
ISBN 10: 6208557518
ISBN 13: 9786208557515
Binding: Soft cover
Condition: New

About this title

Synopsis

Das Spiking Neural Network (SNN) spielt eine wichtige Rolle bei Klassifizierungsproblemen. Obwohl es viele SNN-Modelle gibt, wird das Evolving Spiking Neural Network (ESNN) in vielen aktuellen Forschungsarbeiten verwendet. Evolution�re Algorithmen, vor allem die differentielle Evolution (DE), wurden zur Verbesserung des ESNN-Algorithmus eingesetzt. Viele reale Optimierungsprobleme beinhalten jedoch mehrere widerspr�chliche Ziele. In diesem Buch wurden Harmony Search (HS) und der memetische Ansatz verwendet, um die Leistung von MOO mit ESNN zu verbessern. Folglich wurde Memetic Harmony Search Multi-Objective Differential Evolution with Evolving Spiking Neural Network (MEHSMODE-ESNN) angewendet, um die ESNN-Struktur und die Genauigkeitsraten zu verbessern. Standarddatens�tze aus dem maschinellen Lernen der UCI werden f�r die Bewertung der Leistung dieses verbesserten hybriden Mehrzielmodells verwendet. Die experimentellen Ergebnisse haben gezeigt, dass das Memetic Harmony Search Multi-Objective Differential Evolution with Evolving Spiking Neural Network (MEHSMODE-ESNN) bessere Ergebnisse in Bezug auf Genauigkeit und Netzwerkstruktur liefert.

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