Traditional customer churn prediction treats retention as a static binary classification task. This limits operational value because it fails to address when a customer will leave, why they are leaving, and which intervention is economically viable. No existing framework integrates temporal, explanatory, and prescripti...
The effective resolution of non-deterministic polynomial time hard (NP-hard) combinatorial optimization problems requires a delicate balance between global exploration and local exploitation. While Quantum-Inspired Algorithms (QIAs) leverage principles of superposition to explore vast search spaces, they often lack the...
Raza Hasan, V. Dattana, Salman Mahmood· Applied Informatics· 0 citations
A new continuous optimizer, the Self-adaptive memetic optimizer (SA-MO), designed for high performance with architectural principles from elite competition-winning algorithms, and a novel cross-domain adaptation framework to apply this powerful continuous optimizer to the discrete, combinatorial domain of cloud schedul...
Raza Hasan, Salman Mahmood, S. Palaniappan et al.· Discover Informatics· 0 citations
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