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 17 of 17 for “"Hybrid algorithms"”.
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Hybrid algorithms for distributed constraint satisfaction.
… can be mainly classified into two families of algorithms: systematic search and local search. Systematic search algorithms are complete but may take exponential time. Local search algorithms often converge quicker to a solution for large problems but are incomplete. Problem solving could be …
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Development of Construction Projects Scheduling with Evolutionary Algorithms
Evolutionary Algorithms (EAs) as appropriate tools to optimize multi-objective problems have been applied to optimize construction projects in the last two decades. However, studies on improving the convergence ratio and processing time in the most applied algorithms such as Genetic Algorithm (GA), …
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Optimization Models and Algorithms for Spatial Scheduling
… time. Accordingly, two classes of approximation algorithms were developed: greedy heuristics for finding fast, feasible solutions; and hybrid meta-heuristic algorithms to search for near-optimal solutions. A flexible hybrid algorithm framework was developed, and a number of hybrid algorithms were …
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The Trainability and Expressivity of Quantum Machine Learning Models
… These limitations motivate the study of hybrid quantum-classical algorithms as potential practical use-cases of these devices in the near-term. This thesis is concerned with studying potential use-cases of these hybrid algorithms, determining limitations of algorithms constructed via this …
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Designing Adaptive Ansätze in Quantum Simulation and Geometric Entangling Gates
… of quantum advantage. On the software side, hybrid classical-quantum algorithms are extensively studied as they can be implemented on the current noisy intermediate-scale quantum devices. On the hardware side, researchers are striving for faster and more noise-robustness quantum operations to …
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A framework for hybrid dynamic evolutionary algorithms : multiple offspring sampling (MOS)
Evolutionary Algorithms (EAs) are a set of optimization techniques that have become incredibly popular in the last decades. As they are general purpose algorithms, they have been applied to a wide range of problems, many of them from industrial or scientific disciplines. Several approaches have …
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MULTI-MODEL ALGORITHMS FOR OPTIMIZATION (TRUST REGIONS, NONLINEAR LEAST SQUARES, SECANT, HYBRID METHODS, MODEL SWITCHING)
… NL2SOL of Dennis, Gay and Welsch and the hybrid algorithms of Al-Baali and Fletcher has proven highly effective in practice. Although not explicitly formulated as multi-model methods, many other algorithms implicitly perform a model switch under certain circumstances (e.g., resetting a …
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Hybrid dictionary/statistical text compression algorithms
<p>This thesis is an exploration of hybrid dictionary/statistical algorithms for compressing textual information. The specific intent was to attempt to find an algorithm which would yield greater compression on text files than the algorithm PPMC without requiring significantly greater computing …
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Hybrid DWT-DCT algorithm for image and video compression applications
… transformation. In this work, we propose a hybrid DWT-DCT algorithm for image compression and reconstruction taking benefit from the advantages of both algorithms. The algorithm performs the Discrete Cosine Transform (DCT) on the Discrete Wavelet Transform (DWT) coefficients. Simulations …
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Energy-Efficient and Trustworthy Location-Based Services for Next-Generation IoT
… advance the state of the art by developing hybrid algorithms that combine complementary techniques to improve accuracy and resilience, introducing a novel reliability index to dynamically assess the trustworthiness of each position estimate, and devising security mechanisms to counteract …
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Strategic Environmental Assessment for Municipal Water Demand Based on Climate Change
… Spectrum Analysis (SSA) technique, three hybrid computational intelligence algorithms and an ANN model. These hybrid algorithms include a Lightning Search Algorithm (LSA-ANN), a Gravitational Search Algorithm (GSA-ANN) and Particle Swarm Optimisation (PSO-ANN). The SSA technique is adopted …
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Mathematical and Computational Methods for the n-Body Problem
… optimisation task. Within this setting, novel hybrid algorithms are implemented, most notably the Multi-Population Adaptive Inflationary Differential Evolution Algorithm and the Lattice domain-partitioning scheme, which jointly enable efficient exploration and refinement of the action landscape …
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2022: A Computational Odyssey - Towards a Deeper Understanding of Clustering Streaming Human Activity Recognition Data
… on applying renowned stand-alone clustering algorithms onto a HAR data stream, we developed hybrid algorithms to extract important features for human activity recognition from IoT sensor data, and concluded with an analysis of visualization algorithms that can be used for improving the …
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Sampling based progressive hedging algorithms for stochastic programming problems
… <p>In this dissertation, we develop novel SP algorithms integrating sampling based SAA and decomposition based PHA SP methods. The proposed integrated methods are novel in that they marry the complementary aspects of PHA and SAA in terms of exactness and computational efficiency. Further, the …
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Hybrid Parallel Computing Strategies for Scientific Computing Applications
… Finally, we present work targeting a complete hybrid, parallel computing architecture. With this work we develop and analyze a software framework for generic Monte Carlo simulations implemented on multiple, distributed memory nodes consisting of a multi-core architecture with attached GPUs. …