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Titlebook: Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems; Essam Halim Houssein,Mohamed Abd Elaziz,Laith Abua

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發(fā)表于 2025-3-23 10:32:15 | 只看該作者
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,Elitist-Ant System Metaheuristic for ITC 2021—Sports Timetabling, and high-quality timetables via minimizing constraints violations in a reasonable execution time. This enhanced version is a hybrid elitist-ant system metaheuristic which is tested on a round-robin tournament known as the international timetabling competition-2021 dedicated for sports timetabling.
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,Integration of Machine Learning and?Optimization Techniques for?Cardiac Health Recognition, may be analyzed and provided. Machine learning has been active in the realm of healthcare, from the extraction of information from medical papers to the prediction and diagnosis of a disease. In this perspective, this chapter provides an overview of how to use meta-heuristic algorithm on CVD’s clas
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Hybrid Adaptive Moth-Flame Optimizer and Opposition-Based Learning for Training Multilayer Perceptrark function tests show that AMFOOBL outperforms AMFO, followed by MFO, validating the effectiveness of the proposed approach in terms of accuracy and convergence rate. Second, AMFOOBL is demonstrated on multilayer perceptron‘s (MLP) structural realization and training compared with nine advanced al
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