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Physics-guided machine learning for saturation control across variable hydraulic conditions in heap leaching
A physics-guided machine learning surrogate, conditioned on hydraulic parameters, that predicts hourly saturation profiles in heap …
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Hierarchical Control via MPC-RL for Multi-Timescale Battery Systems
A hierarchical control framework that combines model predictive control (MPC) and reinforcement learning (RL) to separate decisions on …
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DASyR-LLM: Domain-Aware Symbolic Regression with LLMs for Kinetic Model Discovery
DASyR-LLM embeds a large language model inside an iterative symbolic regression algorithm to discover kinetic models. At each iteration …
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From data to decisions: Bayesian modelling and global sensitivity analysis for flotation control
A data-driven framework for interpretable modelling and decision support in flotation. A Gaussian process surrogate trained on …
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