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 2467 for “"Optimisation"”.
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Set-based Particle Swarm Optimisation for Dynamic Optimisation Problems
Many real-world optimisation problems are inherently dynamic, defined by changes in their underlying properties over time. Real-world problems also frequently require optimisation over discrete-valued decision variables. However, the solution of problems that are simultaneously dynamic and …
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Application of Multidisciplinary Design Optimisation to Engine Calibration Optimisation.
… aims to develop a process for engine calibration optimisation by exploiting advanced mathematical methods. Validation of this work is based upon a case study describing a steady-state Diesel engine calibration problem. The calibration optimisation problem seeks an optimal combination of actuator …
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Multi-objective optimisation using sharing in swarm optimisation algorithms
… help of evolutionary computation. Particle Swarm Optimisation (PSO) is a relatively new heuristic that shares some similarities with evolutionary computation techniques, and that recently has been successfully modified to solve multi-objective optimisation problems. In this thesis we first review …
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Holistic, data-driven, service and supply chain optimisation: linked optimisation.
… are automated and are strongly supported by optimisation algorithms - manufacturing optimisation, B2B ordering, financial trading, transportation scheduling and allocation. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems …
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Optimisation over the non-dominated set of a multi-objective optimisation problem
In this thesis we are concerned with optimisation over the non-dominated set of a multiobjective optimisation problem. A multi-objective optimisation problem (MOP) involves multiple conflicting objective functions. The non-dominated set of this problem is of interest because it is composed of the …
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Compact Dynamic Optimisation Algorithm
… recent years, the field of evolutionary dynamic optimisation has seen significant increase in scientific developments and contributions. This is as a result of its relevance in solving academic and real-world problems. Several techniques such as hyper-mutation, hyper-learning, hyper-selection, …
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Optimisation of neonatal ventilation
Background: Infants born prematurely or at term may unfortunately suffer morbidity from ventilator related complications. New ventilation techniques have been developed aimed at reducing that morbidity, but have yet to be fully evaluated. <br/>Aim: To optimise the delivery of new techniques using …
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Optimisation of chaotic thermoacoustics
… is on stability, sensitivity and gradient-based optimisation of the chaotic thermoacoustic system. First, we propose covariant Lyapunov vector analysis as a tool to calculate the stability of chaotic acoustics, making connections with eigenvalue and Floquet analyses. Second, covariant Lyapunov …
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Quality optimisation of carrot juice
The carrot is one of the most widely consumed root vegetables, both in raw and processed forms and offers various nutritional benefits with the firesh product being low in energy and a good source of fibre, potassium and other minerals. Of all the vegetables, it is one of the richest sources of …
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Opinion Analysis through Constraint Optimisation
… learnt from review data using constraint optimisation. Thirdly, instead of providing just a binary positive or negative output, our model can be used to provide a graded overall sentiment. Our experiments show that our model provides state-of-the-art opinion classi�cation.
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Maintenance optimisation for wind turbines.
… for wind turbines are determined. Maintenance optimisation is a means to determine the most cost-effective maintenance strategy. Field failure and maintenance data of wind turbines are collected and analysed using two quantitative maintenance optimisation techniques; Modelling System Failures …
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Issues in on-line optimisation
In general, on-line optimisation can be defined as the on-line process of finding the optimum set-points of the system. Several areas might be concerned in this procedure. This thesis evaluates algorithms for on-line Optimisation. Techniques for steady-state detection, static data reconciliation, …
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Compiler Optimisation of Typeless Languages
… We show how we can subsume some traditional optimisation techniques, such as constant propagation, into more powerful methods that take advantage of value range information to optimise a wider variety of cases. We also show how this information can be used to recover most of the benefits of …
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Geometric numerical integration for optimisation
… we study geometric numerical integration for the optimisation of various classes of functionals. Numerical integration and the study of systems of differential equations have received increased attention within the optimisation community in the last decade, as a means for devising new optimisation …
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Reinforcement learning for telescope optimisation
Reinforcement learning is a relatively new and unexplored branch of machine learning with a wide variety of applications. This study investigates reinforcement learning and provides an overview of its application to a variety of different problems. We then explore the possible use of reinforcement …
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Semantic optimisation in datalog programs
… As is the case with all declarative languages, optimisation is necessary to improve the efficiency of programs. Semantic optimisation uses meta-knowledge describing the data in the database to optimise queries and rules, aiming to reduce the resources required to answer queries. In this thesis, …
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Robustness of bond portfolio optimisation
… the Markowitz (1952) approach to bond portfolio optimisation is robust. The results indicate that the superior capability of an essentially affine model to forecast expected returns outweighs real-world parameter estimation issues; and that the estimation and mean-variance optimisation procedures …
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