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 380 for “"Cost Function"”.
-
An empirical estimation of a cost function for elementary and secondary education
… of current data, by means of a statistical cost function utilizing cross-section data on New York State school districts.</p> <p>This dissertation takes into account differences in socio-economic background across school districts and tests the hypothesis that students of differing …
-
From Static to Adaptive: Dynamic Cost Function Weight Adaptation in Hierarchical Reinforcement Learning for Sustainable 6G Radio Access Networks
… solutions rely on static thresholds or fixed cost function weights, limiting adaptability in dynamic environments. This thesis investigates how cost function design and weight adaptation influence the trade-off between energy consumption and Quality of Service (QoS) degradation in Deep …
-
Minimum description length, regularisation and multi-modal data
… Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit …
-
Sensitivities in Option Pricing Models
… as a minimization problem for an appropriate cost function to minimize the difference between the solution of the model and the market observations. Efficient gradient based optimization requires accurate gradient estimation of the cost function. In this thesis we highlight the adjoint method …
-
A gradient optimization approach to adaptive multi-robot control
… sensor coverage. This example gives rise to a cost function that is shown to be of a surprisingly general nature. By changing a single free parameter, the cost function captures a variety of different multi-robot objectives which were previously seen as unrelated. Stable, distributed …
-
K-means landscapes: exploring clustering solution spaces using energy landscape theory
… is ubiquitous in every scientific field. Its cost function supports many possible clustering solutions, and location of low-valued clustering solutions can be challenging. Hence, the topography of the cost function surface is crucial to understanding K-means performance. We present the …
-
Inverse optimal control for deterministic continuous-time nonlinear systems
… optimal control is the problem of computing a cost function with respect to which observed state input trajectories are optimal. We present a new method of inverse optimal control based on minimizing the extent to which observed trajectories violate first-order necessary conditions for …
-
Cost synergies in the commercial banking industry: An econometric examination
… bank product deregulation by examining whether cost synergies, measured by economies of scope, exist in the production of banking services. Using the multiproduct cost economies approach, the existence of overall and product-specific economies of scope and scale were investigated. The major …
-
An Algorithm for multi-output Boolean logic minimization
… in its most generalized form of multi-output function with arbitrary cost criterion. The proposed algorithm is shown to be tighter than the Quine-McCluskey method in its ability to eliminate redundant prime implicants, making it possible to simplify the cyclic tables. In its final form, the …
-
Optimized scheduling of highway work zones
… maintenance work, and minimize the total project cost (i.e., agency cost and road user cost) by optimizing work zone schedules. This dissertation focuses on the maintenance projects on multiple-lane highways. The objective total cost function is formulated while considering a discrete maintenance …
-
A dynamic model of the U.S. cotton market with rational expectations
… cotton farmer and miller problems come from the cost functions. In the cotton cost function a sequential adjustment cost is used while a quadratic cost function is used in the cotton yarns cost function. These optimal decision rules are derived as functions of past values of these decision …
-
Computational Solution Of Inverse Problems With Simulated Annealing
… allows one to reformulate inverse problems as a function minimization involving the associated forward problem. The function to minimize is known as a penalty function or cost function and is defined as the least squares difference between some measured quantity and a quantity computed by the …
-
Initial Orbit Determination of Uncooperative Satellites Using Particle Swarm Optimization From the Point of View of a Novel Observer Orbit
… optimization (PSO) algorithm is explored. Two cost functions for the PSO algorithm are investigated. The first cost function investigated uses the solution to Lambert’s Problem to estimate the initial velocity of the target. The second cost function uses a full estimated state instead of just …
-
Investigation of a Simulated Annealing Cooling Schedule Used to Optimize the Estimation of the Fiber Diameter Distribution in a Peripheral Nerve Trunk
… for finding the global minimum (or maximum) of a cost function which may have many local minima. The set of parameters which comprise the cooling schedule dictate the rate at which simulated annealing reaches its final solution. Converging too quickly can result in sub-optimal solutions while …
-
Optimal Finite Control Set Model Predictive Control Strategies for Induction Motor Drives
… of possible voltage vectors are evaluated by a cost function in an iterative prediction loop. The cost function includes several control objectives, such as minimization of torque and flux errors, the neutral-point voltage of multi-level inverters and inverter switching frequency. The control …
-
A comparison of sequential probability ratio and generalized attributes acceptance sampling plans
… The evaluation of the plans is based upon a cost function based upon a combination of the Average Sampling Number (ASN) and the variance of an estimator for the proportion of defective items in a lot. Using a numerical calculation of the defined cost function, the curtailed single sampling …
-
Stochastic shortest path algorithm based on Lagrangian relaxation
… surely have a statistical distribution for its cost function value. The mean and variance, square of standard deviation, values are used as a pair of weight values on a graph to represent the stochastic distribution on each edge. For the stochastic shortest path problem, we observe that the …
-
Multi-Agent Path Planning for Locating a Radiating Source in an Unknown Environment
… Four primary variables are considered: the cost function used to select the agents’ paths, the number of agents in a given scenario, the distance over which the agents are assumed to communicate, and the size of the environment in which the agents are operating. It was found that a cost …
-
Optimal trajectories for fast quantum harmonic transport
… aspects. We present an easily-computed functional of transport trajectories with intuitively interpretable terms which may be used to compare solutions to the quantum harmonic transport problem, but does not require an expensive quantum-mechanical simulation of the ion dynamics. …
-
Time average feedforward control techniques for time varying systems
… controllers. A new technique to estimate the cost function is also presented. This technique is called the Real Time Cost Function Evaluation method. Based upon these new controller design concepts, single channel and multi-channel controllers were developed and experimentally tested. The …
Page 1 of 19