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.
Results
Showing 1 to 20 of 651 for “"Objective function"”.
-
The Objective Function: Science and Society in the Age of Machine Intelligence
… into machine intelligence and re-present it as objective knowledge. These methods trace the chains of dependencies between data collection, processing, and analysis to reveal where and how hidden assumptions about the phenomena being analyzed are advanced.</p> <p>The second half of the …
-
Novel Instance-Level Weighted Loss Function for Imbalanced Learning
… algorithms minimize the binary cross-entropy objective function to determine the final parameter estimates. This objective function assumes an equal class distribution between the minority (i.e. events) and majority (i.e. non-events) classes, which almost never exists in real-world modeling. …
-
Robust Parameter Inversion Using Stochastic Estimates
… Tomography (DOT), even the cost of repeated objective function evaluation can be overwhelming. Despite the linear (in the state variable) nature of the DOT problem, the nonlinear parameter inversion process is dominated by the computational burden of solving a large linear system for each …
-
Dynamic human-computer collaboration in real-time unmanned vehicle scheduling
… task allocation usually have an a priori coded objective function that only takes into account pre-determined variables with set weightings. Due to the complex, time-critical, and dynamic nature of command and control missions, brittleness due to a static objective function could cause higher …
-
Inverse optimization of discrete-time systems applied to human locomotion
… problem of inverse optimization is to find the objective function that is being minimized, given knowledge of the constraints and observations of local minima. In this thesis, we consider the special case in which the objective function is a linear combination of known basis functions weighted …
-
Optimization by Gaussian smoothing with application to geometric alignment
… that global optimization of a nonconvex function, in general, is computationally intractable. Nevertheless, many objective functions that we need to optimize may be nonconvex. In practice, when working with such a nonconvex function, a very natural heuristic is to employ a coarse-to-fine …
-
Objective functions for nonlinear structural analysis
An objective function that is suitable for both stable and unstable equilibrium states since it is guaranteed to assume a relative minimum at any equilibrium state is presented. The objective function, which is the inner product of the equations of equilibrium (algorithm 2), is compared with …
-
A NEW ZEROTH-ORDER ORACLE FOR DISTRIBUTED AND NON-STATIONARY LEARNING
… in the loop. In these problem settings, the objective function to optimize does not have an explicit math- ematical form and therefore its gradient cannot be obtained. This invalidates all gradient-based optimization approaches. On the other hand, ZO methods approxi- mate the gradient by …
-
A Probabilistic Study of 3-SATISFIABILITY
… by a finite set of solutions together with an objective function value assigned to each solution. Local search algorithms provide useful tools for addressing a wide variety of intractable discrete optimization problems. Each such algorithm offers a distinct set of rules to intelligently exploit …
-
Green soybeans: Physical and rheological properties, optimization of harvest time, and mechanical harvesting and shelling
… The models were then combined to develop an objective function to predict the ""value"" of green soybeans as a function of seed development. The value was optimized by taking the first and the second derivatives of the objective function. The value of Hack variety was found to be optimized at …
-
Optimal passive nonlinear damper design methodology for road race application
… model for simulation, identification of the objective function which maximizes lateral acceleration based on tire data, optimization of the objective function by varying damping and inertance, identification of mode shapes and root locus analysis. No closed form solution exists for an optimal …
-
Higher-Order Regularization in Computer Vision
… vision models lies the minimization of an objective function consisting of a sum of functions with few arguments. The order of the objective function is defined as the highest number of arguments of any summand. To reduce ambiguity and noise in the solution, regularization terms are …
-
An evaluation of macroeconomic policies in Greece within an optimal control theory framework
… monetary) policies on a set of macroeconomic objectives, giving explicit consideration to the alternative modes by which the budget deficits (or surpluses) are financed. The extent to which quantitative reductions in the share of the public sector is compatible with these objectives is also …
-
Generative Bayesian Optimization for Structured Design
… to find an input that maximizes some real-valued objective function. Typically, no mathematical form is available for this objective function, and it may be expensive to evaluate, making it a black-box. Many practical scientific discovery problems can be framed as black-box optimization. For …
-
Quantile regression and the duration of unemployment
… relax the conventional linear specification of functional form, and the quantile regression estimator of the parameters of the transformed and censored regression models is presented. Both the $N\sp{1/2}$-consistency and the asymptotic normality of quantile estimator are derived for nonlinear …
-
Selected optimization procedures for CFD-based shape design involving shock waves or computational noise
… of the design problem may cause the objective function to be non-smooth. Methods for robust optimization of the nonsmooth functions are presented. The dissertation is divided into two parts, The first part investigates a simple model problem involving quasi-one-dimensional flow in a …
-
Dynamic decision-making under uncertainties: algorithms based on linear decision rules and applications in operating models
… To extend the LDR method to nonlinear objectives, two methods are proposed. The first is an iterative LDR (ILDR) method that tackles general concave differentiable nonlinear terms in the objective function. The second treats quadratic terms in the objective function by a Second-Order …
-
Calibration of a microscopic traffic simulator
… and observed values of speed. Two different objective function forms were formulated for quantifying the deviation between the simulated and observed values. The search space and the optimum parameter values for the two objective function forms were compared. The effect of stochasticity in …
-
The nonlinear differential semblance algorithm for plane waves in layered media
… existence of many spurious local minima of the objective function for typical data, which lack low-frequency energy. To recover the low-frequency lacuna of typical data, I formulate waveform inversion into a differential semblance optimization (DSO) problem with artificial low-frequency data as …
-
Assessing the Finite-Time Performance of Local Search Algorithms
… where B is a predetermined threshold for the objective function value. It is difficult to assess a priori the effectiveness of local search algorithms, which makes the process of choosing parameters to improve their performance difficult. This dissertation introduces the B-acceptable solution …
Page 1 of 33