We study some nonlinear optimal control problems under state constraint. We construct extremal flows by differential-algebraic equations to solve an optimal control problem subject to mixed ...

Individuals living in urban cities are experiencing the combined effect of increasing temperatures and poor air quality, often referred to as the urban heat dome. Pregnant mothers and their unborn ...

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Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

School of Mathematics, Liaoning Normal University, Dalian, China. In recent years, research in this field has continued to deepen, involving multiple different directions. As an example, a research ...

In the realm of competitive programming, both human participants and artificial intelligence systems encounter a set of unique challenges. Many existing code generation models struggle to consistently ...

Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA, United States In this work, we propose a new Gaussian process (GP) regression framework that enforces the physical ...

Abstract: Existing nonlinear guidance methods are difficult to reconcile performance optimality with stability assurance. This study proposes a concept of robust incremental learning for approximate ...

The artificial intelligence start-up said the new system, OpenAI o3, outperformed leading A.I. technologies on tests that rate skills in math, science, coding and logic. By Cade Metz Reporting from ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...