Abstract: Planning smooth trajectories through a sequence of waypoints under nonconvex constraints is challenging due to the coupling between coefficient optimization and time allocation. Existing ...
The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...
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How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
Abstract: This paper presents an extended gradient-based optimization framework for optimal control problems governed by general conformable fractional derivatives (GCFDs), which unify various ...
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