Results 11 to 20 of about 599 (109)
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT In the present investigation, a mathematical model with vaccination, treatment, and environmental impact under real data is presented. Initially, we present the model without any interventions, followed by an examination of its equilibrium points.
Bashir Al‐Hdaibat +4 more
wiley +1 more source
Duality for Evolutionary Equations With Applications to Null Controllability
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT We study evolutionary equations in exponentially weighted L2$$ {\mathrm{L}}^2 $$‐spaces as introduced by Picard in 2009. First, for a given evolutionary equation, we explicitly describe the ν$$ \nu $$‐adjoint system, which turns out to describe a system backwards in time. We prove well‐posedness for the ν$$ \nu $$‐adjoint system. We then apply
Andreas Buchinger, Christian Seifert
wiley +1 more source
On the Mean‐Field Limit of Consensus‐Based Methods
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT Consensus‐based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivative free sampling method referred to as consensus‐based sampling (CBS). In this paper, we investigate the “mean‐field limit” of a class of consensus methods, including
Marvin Koß, Simon Weissmann, Jakob Zech
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Interaction of Dirac δ$$ \delta $$‐Waves in the Inviscid Levine and Sleeman Chemotaxis Model
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT This article investigates interactions of δ$$ \delta $$‐shock waves in the inviscid Levine and Sleeman chemotaxis model ut−λ(uv)x=0$$ {u}_t-\lambda {(uv)}_x=0 $$, vt−ux=0$$ {v}_t-{u}_x=0 $$. The analysis employs a distributional product and a solution concept that extends the classical solution concept.
Adelino Paiva
wiley +1 more source
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT We study eigenvalue problems for the de Rham complex on varying three‐dimensional domains. Our analysis includes the Helmholtz equation as well as the Maxwell system with mixed boundary conditions and non‐constant coefficients. We provide Hadamard‐type formulas for the shape derivatives under weak regularity assumptions on the domain and its ...
Pier Domenico Lamberti +2 more
wiley +1 more source
Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance
Naval Research Logistics (NRL), EarlyView.ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley +1 more source
Optimal Homogeneous ℒp$$ {\boldsymbol{\mathcal{L}}}_{\boldsymbol{p}} $$‐Gain Controller
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Nonlinear ℋ∞$$ {\mathscr{H}}_{\infty } $$‐controllers are designed for arbitrarily weighted, continuous homogeneous systems with a focus on systems affine in the control input. Based on the homogeneous ℒp$$ {\mathcal{L}}_p $$‐norm, the input–output behavior is quantified in terms of the homogeneous ℒp$$ {\mathcal{L}}_p $$‐gain as a ...
Daipeng Zhang +3 more
wiley +1 more source
Coevolutionary Neural Dynamics With Learnable Parameters for Nonconvex Optimisation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Nonconvex optimisation plays a crucial role in science and industry. However, existing methods often encounter local optima or provide inferior solutions when solving nonconvex optimisation problems, lacking robustness in noise scenarios. To address these limitations, we aim to develop a robust, efficient and globally convergent solver for ...
Yipiao Chen +3 more
wiley +1 more source
AGT: Efficient Offline Reinforcement Learning With Advantage‐Guided Transformer
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Offline reinforcement learning (RL) is a paradigm that seeks to train policies directly based on fixed datasets derived from previous interactions with the environment. However, offline RL faces critical challenges in environments characterised by sparse rewards and datasets dominated by suboptimal trajectories.
Jiaye Wei +4 more
wiley +1 more source
Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim +2 more
wiley +1 more source