Optimizing Student Performance Prediction Employing Hybrid Random Forest Models Boosted by Nature-Inspired Algorithms

In today's highly competitive educational landscape, it has become essential for institutions to proactively forecast student outcomes, categorize individuals based on their abilities, and actively work towards enhancing their performance in upcoming assessments. Providing students with timely...

書誌詳細
出版年:	Journal of Artificial Intelligence and System Modelling
第一著者:	Ruslan Hemidov
フォーマット:	論文
言語:	英語
出版事項:	Bilijipub publisher 2025-09-01
主題:	education student, random forest classification (rfc) artificial hummingbird algorithm (aha) flow direction algorithm (fda)
オンライン･アクセス:	https://jaism.bilijipub.com/article_230941_cfd4e64e1a5afe8eaeb3e7512de13f35.pdf

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