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Showing 1 to 7 of 7 for “"Nelder-Mead Algorithm"”.
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On the Effects of Noise on Parameter Identification Optimization Problems
… to the measured system output. Optimization algorithms are often used to identify the model parameter values. The presence of noise is difficult to avoid when physical processes are used to calibrate models due to measurement error, model structure error, and errors arising from numerical …
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Calibrating a Latent Order Book Model to Market Data
… as well as a Black-box approach using the Nelder-Mead algorithm. We show that in the diffusion limit, the master equation becomes the LOB reaction-diffusion PDE and certain free-parameters are recoverable with the iterative calibration techniques.
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An inverse problem framework for reconstruction of phonon properties using solutions of the Boltzmann transport equation
… optimization method, referred to as the Nelder-Mead algorithm, with a graduated (multi-stage) optimization framework.
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High Dimensional Non-Linear Optimization of Molecular Models
… applications of the ParOpt software, and the Nelder-Mead algorithm implemented within it, are presented: a coarse-grained (CG) water--ion model, a model for the determination of lipid bilayer structure via the interpretation of scattering data, and a reactive molecular dynamics (ReaxFF) model …
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Fitting Interatomic Potentials to Reproduce Phase Transitions
… melting curve using my own implementation of the Nelder-Mead algorithm. The Ti potential is modified to predict a triple point which is in qualitative agreement with experimental predictions. To calculate phase transitions, I use the nested sampling algorithm which was already established in the …
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Agile load transportation systems using aerial robots
… investigated method we use is based on the Nelder-Mead algorithm which is an optimization technique used for nonlinear unconstrained optimization problems. This method is model free and it can be used for offline or online generation of the swing-free trajectories for the suspended load. …
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Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology
… methods of optimisation (both genetic algorithms and genetic programming) in providing usable methods for optimisation in design and in complex nonlinear modelling applications that do not involve real-time problems. Another topic, considered both in the context of system modelling and …