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 16 of 16 for “"Function optimization"”.
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GOssiping Optimization Framework (GOOF): A decentralized P2P architecture for function optimization
This thesis discusses the implementation of function optimization algorithms through distributed and decentralized processing in a peer-to-peer fashion. Our research is focused on a fully decentralized, general purpose P2P environment, with no special or ad-hoc facility for executing optimization …
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Niching methods for genetic algorithms
… classification and machine learning, multimodal function optimization, multiobjective function optimization, and simulation of complex and adaptive systems.
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Fault-tolerant consensus in directed graphs and convex hull consensus
… related problems, such as vector consensus and function optimization with the initial convex hull as the domain.
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Error Resilient Video Coding Using Bitstream Syntax And Iterative Microscopy Image Segmentation
… Our second method selectively uses a shape-based function optimization approach and a 2D marked point process simulation, to quantify nuclei by their locations and sizes. Experimental results exhibit that our proposed methods are effective in addressing the aforementioned challenges.</p>
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Generating secret in a network
… mutual dependence. New identities in submodular function optimization and matroid theory are discovered in proving these results. A framework is also developed to view matroids as graphs, allowing certain theory on graphs to generalize to matroids. In order to study cooperation schemes in a …
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Modelling and Multi-objective Optimization of Continuous Protein Recovery in Liquid-Solid Circulating Fluidized Bed (LSCFB)
… focused on the modelling and multi-objective optimization of LSCFB system for continuous protein recovery process. A mathematical model was developed considering the protein adsorption and desorption characteristics, liquid-solid mass transfer and the hydrodynamics of the LSCFB, to predict the …
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Electrochemical Model Based Fault Diagnosis of Lithium Ion Battery
A gradient free function optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized in parameter identification of the electrochemical model of a Lithium-Ion battery having a LiCoO2 chemistry. Battery electrochemical model parameters are subject to change under severe …
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Load balancing using cell range expansion in LTE advanced heterogeneous networks
… cell range expansion (CRE) and network utility optimization techniques to ensure fair sharing of load in a macro and pico cell LTE Advanced heterogeneous network. The aim is to investigate how to use an adaptive cell range expansion bias to optimize Pico cell coverage for load balancing. …
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Machine learning for selecting parallel I/O benchmark applications
… these bottlenecks and to guide the performance optimization of poor performing applications, is therefore an important problem. We investigate the use of submodular function maximization as a way to select a set of I/O benchmark applications using measures of similarities between applications …
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Development Of New Algorithms For Exploring The Potential Energy Landscape Of Chemical Reactions
… benchmarked against a standard transition state optimization approach utilizing a test set of 20 reactions, with energies computed at both semiempirical and density functional theory levels of theory. Chapter 4 is a collection of 3 new, alternative approaches (Flowchart Hessian updating, Scaled …
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Optimal Inference for Distributed Detection
… decision strategies for non-affine decision functions. Consequently, in a detection problem based on a non-affine decision function, establishing optimality of a given decision strategy, such as a generalized likelihood ratio test, is often difficult or even impossible.</p> <p>In this thesis …
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A radial basis function approach to pricing and hedging options incorporating transaction costs
Nonparametric methods of pricing options have been available for some time, providing a viable alternative to traditional parametric methods. A general class of methods known as learning networks has been making significant inroads in option pricing literature. This thesis will adopt McLoone's …
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Parsimonious, Risk-Aware, and Resilient Multi-Robot Coordination
… the coordination achieved by means of submodular function optimization. Submodularity encodes the diminishing returns property that arises in multi-robot coordination. For example, the marginal gain of assigning an additional robot to track the same target diminishes as the number of robots …
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Automated small molecule synthesis for accelerated discovery of photo- and electroactive organic materials
… have transformed materials discovery, enabling optimization of functional properties and determination of fundamental principles in molecular design. A key innovation is the closed-loop transfer (CLT) method, which integrates closed-loop workflows with physics-based feature selection and …
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On numerical methods in quantum spin systems
… issues of representation of variational wave functions and their optimization. In chapter 5, I present a numerical study on the embedding of an exactly solvable point in a phase diagram of an extended Heisenberg model on a kagome lattice. Chapter 6 studies a quantum Heisenberg model on the …
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Yield Curves and Macro Variables Interactions and Predictions
… based on: Granger Causality, Impulse Response Function and Variance Decomposition. Afterwards, we predicted yield curves based on ANN Regression Multitask learning, and lastly, we predicted our five macro variables based on three different ANN Classifiers, in order to generalize and present …