Results 71 to 80 of about 3,465,725 (297)
, 2018 Complex optimization problems can be tackled by means of mathematical programming methods as well as by means of (meta)heuristic methods. On the one hand, mathematical programming methods give us a guarantee of optimality while (meta)heuristic methods do
Rodríguez, Nibaldo +3 more
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Production, 2001 Este artigo apresenta uma experiência real de implantação de um modelo de Pesquisa Operacional para realizar a alocação de referees para avaliar trabalhos submetidos a um congresso de grande porte.
Flavio Cesar F. Fernandes, Evelyn Rios
doaj +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
Mathematical Optimization for Machine Learning
Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete ...
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Existence of solutions for discontinuous systems of Stieltjes differential equations
Electronic Journal of Qualitative Theory of Differential EquationsWe introduce new transversality conditions in terms of derivatives with respect to a nondecreasing function $g: \mathbb R \longrightarrow \mathbb R$, and we use them to prove the existence of solutions for discontinuous systems of Stieltjes differential ...
Víctor Cora, Rodrigo López Pouso
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
σ-porosity in monotonic analysis with applications to optimization
Abstract and Applied Analysis, 2005 We introduce and study some metric spaces of increasing positively homogeneous (IPH) functions, decreasing functions, and conormal (upward) sets. We prove that the complements of the subset of strictly increasing IPH functions, of the subset of strictly ...
A. M. Rubinov
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Engenharia Agrícola, 2011 Modelos matemáticos computacionais de otimização de redes de irrigação, sob vazão em marcha, capazes de fornecer dados hidráulicos, são importantes para a verificação do comportamento do sistema quanto à distribuição da carga hidráulica (energia) e da ...
Francisco F. N. Marcuzzo, Edson Wendland
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A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source