Phantom-Driven Hybrid Deep Learning Classifier Systems for Real-Time Decision Making

Learning Classifier Systems are recognized as a hybrid framework that integrates rule-based interpretability with adaptive learning. However, classical LCS models experience performance degradation when handling high-dimensional, multichannel dynamic data, particularly in real-time applications. Thi...

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Главные авторы:	MohammadReza DehghaniMahmoudAbadi, Elham DehghanTezerjani
Формат:	Artigo
Язык:	Persa
Опубликовано:	Yazd University 2026-04-01
Серии:	پژوهش‌های نظری و کاربردی هوش ماشینی
Предметы:	learning classifier systems (lcs) layer phantom deep learning explainable artificial intelligence (xai) streaming data
Online-ссылка:	https://abmir.yazd.ac.ir/article_4008_ed1989edfd2fecd1000baa235282881f.pdf
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