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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 64 for “"Fitness Function"”.
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OBJECTIVELY MEASURED PHYSICAL ACTIVITY LEVELS AND THEIR RELATIONSHIP TO PHYSICAL FITNESS/FUNCTION IN HEART FAILURE PATIENTS
… the relationship of PA levels to other physical fitness/functional measures, and determine if there are significant differences between objectively measured PA levels and well-established prognostic measures in this population.
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Development of a Wavelet -Based Algorithm and Fitness Function for Computational and Experimental Quantum Control of Intramolecular Vibration Redistribution
… interaction with tailored laser pulses, a simple fitness function for control, based only on knowledge of P(t), is developed. Variations of this fitness function are tested in several scenarios to check for robustness and learn about the mechanism of control. Additionally, key features of the …
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Towards realising multimodal robots
… of co-evolutionary robotics. The first is in fitness function development, which plays an integral part in selecting parents for mating during evolution. The effect of an incremental fitness function based on established algorithmic techniques from specific task domains of robotics is studied. …
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Genetic Algorithm Stream Cipher Key Generation Using NIST Functions
… cipher when individual and combinations of fitness functions are used. Furthermore, this study identified which fitness function is the best for a specific scenario. For the genetic algorithm, the fitness tests are thirteen of the tests defined in NIST SP 800-22rla. The thirteen different …
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An Improved Genetic Algorithm for the Optimization of Composite Structures
… approximations of the objective and constraint functions individually instead of direct approximations of the overall fitness function. The primary motivation for the proposed improvements is the nature of the fitness function in constrained engineering design optimization problems. Since GAs …
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Utilization of Genetic Algorithms and Constrained Multivariable Function Minimization to Estimate Load Model Parameters from Disturbance Data
… Genetic algorithms and constrained multivariable function minimization are global and local optimization tools used to extract static and dynamic load model parameters from postdisturbance data. The genetic algorithm's fitness function minimizes the difference between measured and calculated real …
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Emerging Variants and Fading Immunity: Analyzing the Impact in Epidemic Modeling
… showing that when using the epidemic spread fitness function there is a tendency to produce more variants than when using the epidemic severity fitness function, highlighting the virus's need to mutate in response to existing immunity. When the population is dominated by younger individuals, …
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Array signal processing for source localization and enhancement
… SNR gains (WNG’s) form the basis of the PSO’s fitness function. Another important consideration in the optimal weight design are several regularization parameters. By including those parameters in the particles, we optimize their values as well in the operation of the PSO. The proposed method …
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Cascaded Digital Refinement for Intrinsic Evolvable Hardware
… construct building blocks, known as Constituent Functional Blocks (CFBs). The CFBs are developed in a cascaded sequence followed by digital evolution of higher-level control of these CFBs to build the final solution for the larger circuit at-hand. One such platform, Cypress PSoC-5LP was utilized …
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The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance.
… assumptions about the structure of the black-box fitness function they optimise. A review of the literature shows that understanding of structure and linkage is helpful to the design and analysis of heuristics. The aim of this thesis is to investigate the role that problem structure plays in …
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Optimizing Groundwater Remediation Designs Using Dynamic Meta-Models and Genetic Algorithms
… called Noisy-AMGA, minimizes the expected fitness function with a constrained reliability level. As in AMGA, the meta-models in Noisy-AMGA are online updated but they are trained to predict the expected outputs. The method was applied to two remediation case studies, where the primary …
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Orbital Constellation Design and Analysis Using Spherical Trigonometry and Genetic Algorithms: A Mission Level Design Tool for Single Point Coverage on Any Planet
… based on a multi-objective optimization function. Each constellation will be evaluated on a normalized fitness scale to determine optimization. The performance objective functions are based on average coverage time, average revisits, and a minimized number of satellites. To adhere to a …
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DEUM: a framework for an estimation of distribution algorithm based on Markov random fields.
… distribution. The thesis describes a model of fitness function that approximates the energy in the Gibbs distribution, and shows how this model can be fitted to a population of solutions to estimate the parameters of the MRF. The estimated MRF is then sampled to generate the next population. …
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Evolving Variability Tolerant Logic
… The genetic algorithm uses a multi-objective fitness function to allow a number of circuit characteristics to be considered in the evolution process. The system is tested using different standard-cell libraries from open-source and commercial providers, with developments and alterations to the …
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A Prediction Modeling Framework For Noisy Welding Quality Data
… to reduce the computational cost when the fitness or constraints functions are associated with computationally expensive tasks or analyses. In our case, the objective function is associated with constructing bagging SVR models with candidate sets of hyper-parameters. Therefore, in regards …
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Modeling, simulation and visualization of stability and support operations using coevolution: Concepts and environment
… strategies benefits from examining changes in fitness function, instead of the fitness function directly, as is generally done for one-sided genetic algorithms. As inputs, a military expert defines a scenario by specifying an environment of locales, factions and entities that belong to multiple …
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Optimisation of electrical machines using data-driven dynamic thermal models and surrogate-based multi-objective evolutionary algorithms.
… candidate designs, making them impractical when fitness function evaluations are computationally expensive. To address these challenges, we develop low-complexity, data-driven Linear Regression models for estimating motor component temperatures as an alternative to traditional thermal models that …
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Automated test sequence generation for finite state machines using genetic algorithms
… of the transition conditions and a number of fitness function algorithms are defined. An empirical study of the effectiveness on real FSA based systems and example FSAs provides some interesting positive results. The use of genetic algorithms (GAs) makes these problems scalable for large FSAs. …
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Robust nonlinear controller based on set propagation
… a driven pendulum with actuator constraints. The fitness function to be maximized is the probability of each state of the system being controlled to the setpoint without being perturbed to regions that are more iterations away from the setpoint. The u-surface is designed by finding all the states …
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Investigating genetic programming with novelty and domain knowledge for program synthesis
… Grammatical Evolution uses and to supplement its fitness function. Additionally, we investigate the compounding impact of this knowledge and novelty search. The resulting approaches exhibit improvements in accuracy on a majority of problems in the field's benchmark suite of program synthesis …
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