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 73 for “"Evolutionary computation"”.
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Evolutionary Computation and Experimental Design
… to produce good solutions quickly. Many evolutionary computation and experimental design methods are considered before genetic algorithms and evolutionary operation are combined to produce novel optimisation algorithms. A novel piece of software is created to run two and three factor …
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Evolutionary computation applied to combinatorial optimisation problems
… Tradeoff) function, the user can balance the computational effort against the quality of the solution and thus allow the user to specify exactly what the cost benefit point should be for the search. Results have identified the optimal configuration settings for solving selected TSP problems. …
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Epidemic Simulation and Mitigation via Evolutionary Computation
… and expanded upon. This representation uses an evolutionary algorithm and is modified to include new local edge operations improving the performance of the system across several test problems. These problems include an epidemic's duration, spread through a population, and closeness to past …
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Advances in Hybrid Evolutionary Computation for Continuous Optimization
Evolutionary Algorithms (EAs) are a set of optimization techniques that have become highly popular in recent decades. One of the main reasons for this success is that they provide a general purpose mechanism for solving a wide range of problems. Several approaches have been proposed, each of them …
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An Evolutionary Computation Model of Intracellular Signaling Networks
We use evolutionary computation (EC) methods to simulate the evolution of a particular class of intracellular signaling networks. This class of signaling networks mimics the cellular state transition (or mode switch) in a living cell in response to a specific number of prerequisites. Two different …
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High-performance evolutionary computation for scalable spatial optimization
… scalable spatial optimization methods within the evolutionary algorithm (EA) framework. The computational scalability challenge in EA is addressed by developing a parallel EA library that eliminates the costly global synchronization in massively parallel computing environment and scales to 131,072 …
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Intelligent network intrusion detection using an evolutionary computation approach
… attacks. To meet the requirements of a good IDS, computational intelligence methods have attracted considerable interest from the research community. This thesis explores a solution to automatically generate compact rulesets for network intrusion detection utilising evolutionary computation …
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Application of evolutionary computation to open channel flow modelling
This thesis examines the application of two evolutionary computation techniques to two different aspects of open channel flow. The first part of the work is concerned with evaluating the ability of an evolutionary algorithm to provide insight and guidance into the correct magnitude and trend of the …
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Evolutionary Computation for Dynamic Optimisation Problems with Different Requirement Satisfaction
… or maintaining population diversity. Studies in Evolutionary Dynamic Optimization (EDO) typically allow for many individual evaluations before the environment changes. When the environment changes very quickly, unsolved challenges arise where typical population-based algorithms may be negatively …
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The Proteomics Approach To Evolutionary Computation: An Analysis Of Pr
As the complexity of our society and computational resources increases, so does the complexity of the problems that we approach using evolutionary search techniques. There are recent approaches to deal with the problem of scaling evolutionary methods to cope with highly complex difficult problems. …
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Evolutionary Computation Techniques for Intrusion Detection in Mobile Ad Hoc Networks
… help with this task. We investigate the use of evolutionary computation techniques for synthesising intrusion detection programs on MANETs. We evolve programs to detect the following attacks against MANETs: ad hoc flooding, route disruption, and dropping attacks. The performance of evolved …
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Design and implementation of evolutionary computation algorithms for volunteer compute networks
We implemented a distributed evolutionary computation system titled EvoGPJ Star (EGS) and deployed the system onto Boinc, a volunteer computing network (VCN). Evolutionary computation is computationally expensive and VCN allows more cost-effective cluster computing since resources are donated. In …
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Investigating Reinforcement Learning and Evolutionary Computation for Games with Stochasticity and Incomplete Information
… an application of reinforcement learning and evolutionary computation for solving complex games with incomplete information and stochasticity. Although there has been significant recent progress on AI game players, traditional deep reinforcement learning methods have mainly shown success in …
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Using signal processing, evolutionary computation, and machine learning to identify transposable elements in genomes
… serve as molecular fossils, giving clues to the evolutionary history of the organism. TE's are often challenging to identify because they are fragmentary or heavily mutated. In this thesis, novel features for the detection and study of TE's are developed. These features are of two types. The …
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User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation
… image thresholding tasks by using an interactive evolutionary optimization approach. Eye illusion and image enhancement are subjective human perception-based issues, so, there is no proposed analytical fitness function for them. Their optimization is only possible through interactive methods. The …
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Evolutionary computation based multi-objective design search and optimization of spacecraft electrical power subsystems
… and multi-objective search techniques, such as evolutionary computation, offer a possibility of accelerating and improving this design cycle through a machine-automated design procedure. This thesis addresses the key issue of intelligent design automation and optimization of spacecraft power …
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ENAMS: Energy optimization algorithm for mobile wireless sensor networks using evolutionary computation and swarm intelligence.
… Mobile Sensor networks) which is based on the Evolutionary Computation and Swarm Intelligence to increase the life time of mobile wireless sensor networks. The presented algorithm is suitable for large scale mobile sensor networks and provides a robust and energy- efficient communication …
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The application of software visualization technology to evolutionary computation: a case study in Genetic Algorithms
Evolutionary computation is an area within the field of artificial intelligence that is founded upon the principles of biological evolution. Evolution can be defined as the process of gradual development. Evolutionary algorithms are typically applied as a generic problem solving method, searching a …
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Multi-objective evolutionary computation for the portfolio optimization problem with respect to environmental, social, and governance criteria
… best. A system leveraging Multi-Objective Evolutionary Computation, specifically MOEA/D, was proposed to produce highly performant portfolios tailored to an individual’s ESG preferences given a custom survey. The survey, written using the greater context of other risk and ESG relevant …
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