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1
Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010)
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masterThesis -
2
Scatter search for protein structure prediction. (c2008)
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masterThesis -
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…Most such models are constructed using statistical or machine learning techniques. …”
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masterThesis -
5
Detection of statistically significant network changes in complex biological networks
Published 2017“…</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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masterThesis -
7
Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. Combining statistical and ranking analyses confirms that the Levenberg–Marquardt (LM) is the most efficient optimization technique for training the MLPNN model. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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doctoralThesis -
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R<sup>2</sup>), were used to assess the prediction accuracy of the models. …”
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A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…The simulation results show good tracking performance in the presence of noise with erroneous model parameters and noise statistics. An open-loop control is also proposed to improve the tracking rate of the proposed ILC algorithms.…”
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Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle
Published 2017Get full text
doctoralThesis -
15
A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading
Published 2020“…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. The outcomes from the algorithm are based on clustering the solar insolation values and then applying a genetic algorithm optimisation to indicate the optimum BIPV array layout for maximum yield.…”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
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Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes
Published 2019“…The best-fitting mathematical model is then enhanced using a Kalman filtering (KF) algorithm to account for the statistics of the dynamic and measurements noise sequences in predicted drug release. …”
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Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash
Published 2022“…The calculations are performed with the electrolyte Statistical Associating Fluid Theory with the Mie potential of variable range (eSAFT-VR Mie) equation of state but the proposed methods are general and could be used with any other thermodynamic model.…”
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Evolutionary support vector regression for monitoring Poisson profiles
Published 2023“…This paper aims to monitor Poisson profile monitoring problem in Phase II and develops a new robust control chart using support vector regression by incorporating some novel input features and evolutionary training algorithm. The new method is quicker in detecting out-of-control signals as compared to conventional statistical methods. …”