Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 32 for “"local linear"”.
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Modelling and Control of Chemical Processes using Local Linear Model Networks
… to chemical reactors and processes are nonlinear. Therefore, the aim of this research is to overcome these challenges by applying a local linear model networks technique to identify and control temperature, pH, and dissolved oxygen. The reactor studied exhibits a nonlinear function, which …
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A sequential adaptive sampling technique based on a local linear model for computer experiment applications
… for surrogate model (SM) applications based on a local linear model. This technique, called Nearest Neighbors Adaptive Sampling (NNAS), is conceived to be conceptually simple, computationally robust, and easy to apply, all characteristics that are crucial for effective surrogate modeling …
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Smooth regression quantile estimation
… thesis, attention will be mainly focused on the local linear kernel regression quantile estimation. Different estimators within this class have been proposed, developed asymptotically and applied to real applications. I include algorithmdesign and selection of smoothing parameters. Chapter 2 …
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Model-robust quantal regression
… methods, such as kernel regression or local linear regression, to estimate the dose-response curve, effective doses, and confidence intervals. This research proposes another alternative to analyzing quantal dose-response data called model-robust quantal regression (MRQR). MRQR linearly …
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Image processing in echography and MRI
… method, and abstraction with<br/>clustering and local linear expansion.
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Applications of Forest-Based Machine Learning Methods in Environmental Economics
… cleanup program. The third paper turns to a Local Linear Forest for high‑accuracy prediction, linking Residential Energy Consumption Survey data to high‑resolution climate grids to identify U.S. "dual‑vulnerability" hotspots where households face both extreme temperatures and high energy …
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Advanced techniques for digital image processing
… is proposed here. The enhancement algorithm is a locally adaptive Fourier filter which locates and analyzes the Fourier spectral information and then enhances the identifying features. Thus, it can achieve a better enhancement result than conventional homomorphic FFT techniques. By using a short …
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Three Essays in Applied Econometrics: with Application to Natural Resource and Energy Markets
… dependent data, such as the nonparametric local linear kernel estimator, the Nadraya-Watson estimator, and the k-Nearest Neighbors method developed by Hallin et al. (2004b), Lu and Chen (2002), P.M. Robinson (2011) and Li and Tran (2009). With data sampled on a rectangular grid in a …
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Energy methods for nonsymmetric nonlocal operators
… is to develop the regularity theory for nonlocal parabolic equations. We focus on problems driven by nonlocal operators associated with nonsymmetric bilinear forms. In contrast to the symmetric case, nonsymmetric nonlocal operators have not yet been studied systematically. Our main results …
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Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems
… of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators …
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Development of discontinuous Galerkin method for nonlocal linear elasticity
… materials which, by nature, exhibit a non-local response. The formulation of boundary value problems, in this case, leads to a system of equations involving higher-order derivatives which, in turn, results in requirements of continuity of the solution of higher order. Discontinuous Galerkin …
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Dimension Reduction on Measures of Impulsivity
… from a novel dimension technique known as Local Linear Embedding (LLE). LLE is an analysis of dimension reduction for nonlinear, high dimensional data. By computing neighborhood preserving embeddings, LLE aims to map newly constructed coordinates into a global coordinate structure of a …
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Bias reduction in nonparametric hazard rate estimation
… the automatic boundary adaptive property of the local linear smoother (Fan and Gijbels [13]) we adapt the method to the hazard rate case and we show that it results in estimators with bias at endpoints reduced to the level of interior bias. We then turn our attention to global bias problems. …
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Model robust regression: combining parametric, nonparametric, and semiparametric methods
… nonparametric regression (kernel or local polynomial regression, for example) has no dependence on an underlying parametric model, but instead depends entirely on the distances between regressor coordinates and the prediction point of interest. This procedure avoids the necessity of a …
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Adaptive Functional Data Analysis
… predictor process lies in a potentially nonlinear manifold that is intrinsically finite-dimensional but embedded in an infinite-dimensional function space. We propose a nonparametric estimator built upon local linear manifold smoothing that achieves a polynomial convergence rate and adapts …
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Methods for Quantitatively Describing Tree Crown Profiles of Loblolly pine (<I>Pinus taeda</I> L.)
… a curve. The modeler determines the amount of local curvature to be depicted in the curve. A class of local-polynomial estimators which contains the popular kernel estimator as a special case was investigated. Kernel regression appears to fit closely to the interior data points but often …
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Learning manifolds with the Parametrized Self-Organizing Map and Unsupervised Kernel Regression
… in the field of manifold learning and nonlinear dimensionality reduction. The main text can be divided into three parts, the first of which presents a smoothness-based regularizer that is specifically tuned to the Parametrized Self-Organizing Map (PSOM). The regularization approach makes …
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Advanced Statistical Inference for Stochastic Quasi-Reaction Systems
… randomness of their dynamics. The traditional local linear approximation methods for the estimation of the reaction rates face significant challenges in certain conditions. When the system is observed at short intervals, high correlations between successive observations result in numerical …
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Geometric Dimensionality Reduction
… Geometric Dimensionality Reduction, a non-linear data compression technique that utilizes low dimensional manifolds embedded in dimensional spaces to form composite contraction-and-projection maps. Geometric Dimensionality Reduction is predominantly demonstrated through a novel algorithm …
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