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Discover how PGNAA is transforming materials analysis in mining, cement, and steel. Get expert insights from Thermo Fisher’s ...

Gaussian processes (GPs) have attracted considerable attention in assisting evolutionary algorithms (EAs) to solve computationally expensive optimization problems (EOPs) because they can directly ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

In this study, the gray wolf algorithm was applied to optimize the water-cooled central chilling system operation in a commercial office building. The optimization objective was to maximize the system ...

Abstract: Designing intelligent game strategies for autonomous air combat has suffered from the vast exploration space, lengthy decision-making process, and sparse rewards. Some existing approaches ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...