Výsledky vyhľadávania - "Gradient-based optimisation algorithms"

Robust and structure exploiting optimisation algorithms: an integral quadratic constraint approach Autor Michalowsky, Simon, Scherer, Carsten, Ebenbauer, Christian

“…We consider the problem of analysing and designing gradient-based discrete-time optimisation algorithms for a class of unconstrained optimisation problems…”
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A Novel Supercapacitor Model Parameters Identification Method Using Metaheuristic Gradient-Based Optimization Algorithms Autor Yasin, Ahmad, Dhaouadi, Rached, Mukhopadhyay, Shayok

“…This paper addresses the critical role of supercapacitors as energy storage systems with a specific focus on their modeling and identification. The lack of a…”
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On the efficiency of gradient based optimization algorithms for DNS-based optimal control in a turbulent channel flow Autor Nita, C., Vandewalle, S., Meyers, J.

“…•Limited-memory quasi-Newton methods for DNS-based optimal control are investigated.•Testing is performed in two optimal control studies of turbulent channel…”
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Gradient-based optimization algorithms for networks of reconfigurable sensors Autor de Groot, T.H., Krasnov, O.A., Yarovoy, A.G.

“…A variety of optimization algorithms has been developed for non-linear and non-convex problems in which numerous reconfigurable sensors need to be assigned to…”
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Multiobjective inverse planning for intensity modulated radiotherapy with constraint-free gradient-based optimization algorithms Autor Lahanas, Michael, Schreibmann, Eduard, Baltas, Dimos

“…We consider the behaviour of the limited memory L-BFGS algorithm as a representative constraint-free gradient-based algorithm which is used for multiobjective…”
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Fractional-order optimal control computation: a new gradient-based multi-time-delay optimisation algorithm Autor Ghosh, Indranil, Cheong, Huey Tyng, Teo, Kok Lay

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Efficient and Convergent Natural Gradient Based Optimization Algorithms for Machine Learning Autor Sánchez López, Borja

“…Many times Machine Learning (ML) is casted as an optimization problem. This is the case when an objective function assesses the success of an agent in a…”
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A comparative study on using metaheuristic algorithms for simultaneously estimating parameters of space fractional advection-dispersion equation Autor Maroufi, Halimeh, Mehdinejadiani, Behrouz

“…•The s-FADE parameters were simultaneously estimated using inverse problem method.•Four inverse models were developed based on PSO, CSO, BA, and TLBO…”
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Shape-Programming in Hyperelasticity Through Differential Growth Autor Ortigosa-Martínez, Rogelio, Martínez-Frutos, Jesús, Mora-Corral, Carlos, Pedregal, Pablo, Periago, Francisco

“…This paper is concerned with the growth-driven shape-programming problem, which involves determining a growth tensor that can produce a deformation on a…”
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Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications Autor Bourgeois, F., Labeau, P.E.

“…On one hand, PSA results are increasingly used in decision making, system management and optimization of system design. On the other hand, when severe…”
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Comparison between genetic and gradient-based optimization algorithms for solving electromagnetics problems Autor Haupt, R.

“…This paper compares the application of genetic algorithms and traditional gradient-based algorithms to various optimization problems in electromagnetics…”
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On the concept of a transmission absorber to suppress internal resonance Autor Dylejko, Paul G., MacGillivray, Ian R.

“… The designs are optimised by using a combination of particle swarm and gradient-based optimisation algorithms…”
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Interplay of numerical integration with gradient based optimization algorithms for robust design optimization Autor Kugele, S.C., Watson, L.T., Trosset, M.W.

“…Engineers increasingly rely on computer simulation to develop new products and to understand emerging technologies. In practice, this process is permeated with…”
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Optimising tidal range power plant operation Autor Angeloudis, Athanasios, Kramer, Stephan C., Avdis, Alexandros, Piggott, Matthew D.

“…•We couple simplified power plant operation models with gradient-based optimisation algorithms…”
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A comparison of several gradient based optimization algorithms for PAPR reduction in OFDM systems Autor Koussa, B., Bachir, S., Perrine, C., Duvanaud, C., Vauzelle, R.

“…The aim of this paper is to evaluate and compare different optimization algorithms for Peak to Average Power Ratio (PAPR) reduction in Orthogonal Frequency…”
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Calculation of the structured singular value with gradient-based optimization algorithms on a Lie group of structured unitary matrices Autor Dehaene, J., Cheng Yi, de Moor, B.

“…The structured singular value problem, which is a basic problem in robustness analysis and design of multivariable controllers, can be formulated as an…”
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Adjoint Based Aerodynamic Shape Optimisation Using Kinetic Meshfree Method Autor Malagi, Keshav S., Mamidi, Nischay R., Anil, Nemili, Ramesh, Vasudev, Deshpande, Suresh M.

“…The gradient based optimisation algorithms combined with the finite volume or element based adjoint approaches have been very successful in aerodynamic shape optimization (ASO…”
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Cyber‐Resilient Distributed Energy Resource Control Algorithms for Smart Distribution Grids Autor Panahazari, Mohammad, Yao, Guangming, Zhang, Jianhua, Wang, Jing

“…This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid…”
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Comparative Analysis of Gradient-Based Optimizers in Feedforward Neural Networks for Titanic Survival Prediction Autor Adi Pratama, I Putu, Ni Wayan Jeri Kusama Dewi

“… the Titanic dataset, focusing on the impact of gradient-based optimisation algorithms. Eight optimisers—Batch Gradient Descent…”
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An Improved DE Algorithm to Optimise the Learning Process of a BERT-based Plagiarism Detection Model Autor Moravvej, Seyed Vahid, Mousavirad, Seyed Jalaleddin, Oliva, Diego, Schaefer, Gerald, Sobhaninia, Zahra

“… Deep learning algorithms often use the random weighting method for initialisation, followed by gradient-based optimisation algorithms such as back-propagation for training, making them susceptible…”
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