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 34 for “"Genetic Algorithms (GA)"”.
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Noise, Sampling, and Efficient Genetic Algorithms
As genetic algorithms (GA) move into industry, a thorough understanding of how GAs are affected by noise is becoming increasingly important. Noise affects a GA's population sizing requirements, performance characteristics, and computational requirements. This research develops quantitative models …
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Improving Tree Crown Mapping using Airborne LiDAR with Genetic Algorithms
… use individual tree crown (ITC) recognition algorithms applied to LiDAR point clouds, which have complex parameter sets. Genetic algorithms (GA) have been demonstrated to be excellent function optimizers for very complex search spaces and perform well for parameter tuning. Here, we use GAs to …
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Biomass Characterization and Insulation Optimization Studies
… are found to be close to them. Furthermore, genetic algorithms (GA) can be used to achieve multi-objective optimization entailing maximizing insulation (minimizing heat transfer) and simultaneously maximizing sustainability (minimizing carbon footprint) of a designed insulation structure. The …
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Design of human-like posture prediction for inverse kinematic posture control of a humanoid robot
… Optimization (MOO) is preformed using a Genetic Algorithms (GA) and implemented using the Genetic and Evolutionary Algorithm Matlab Toolbox. The designed system is illustrated on a simple redundant 3 degree of freedom (dof) manipulator and is set up for a more complicated redundant 7 dof …
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Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation
… is based on standard Least-Mean-Squares (LMS) algorithms and on two heuristic optimization techniques, namely, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The use of these algorithms is investigated for suppressing the power line generated 50Hz interference and recovering of …
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Evolutionary computation applied to combinatorial optimisation problems
… the issues associated with conventional genetic algorithms (GA) when applied to hard optimisation problems. In particular it examines the problem of selecting and implementing appropriate genetic operators in order to meet the validity constraints for constrained optimisation problems. …
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Modeling and analysis of off-road tire cornering characteristics
… is presented, as well as the development of Genetic Algorithms (GA) to determine the mathematical relations for the cornering force, self-aligning moment, and overturning moment as functions of important operating factors. Cornering tests were performed for the RHD tire operating over the mud …
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Building load control and optimization
… and Air-Conditioning) systems and by aggregating individual loads based on optimization studies. Emphasis is placed on electricity rates and climate data in California, where electricity costs have been of particular concern. The optimization problem in this research is multi-objective in …
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Design and analysis of genetic algorithms for two classes of spatial optimization
… typically must be separable and differentiable. Genetic algorithms (GA), which allow engineers to optimize problems through the direct implementation of domain-relevant simulations, have demonstrated significant utility for many engineering problems. Additionally, well-posed and executed GA are …
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Developing computational intelligence for helicopter flights control.
… of using inverse simulation and evolutionary algorithms to model systems similar to human process. The aim is to define tasks for the helicopter and have the pilot find control settings that carry out those tasks. The inverse simulation technique for a helicopter generates the control inputs …
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Water resources decision making using meta-heuristic optimization methods
… (SAT). The dissertation's focus was to investigate meta-heuristic (global) optimization methods suitable for developing water resources decision support system (DSS), particularly to optimally design and operate groundwater storage and recovery projects. The effort included developing an …
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Statistical Experimental Design Framework for Cognitive Radio
… with artificial intelligence decision-making algorithms. Current architectures trend towards hybrid combinations of heuristics, such as genetic algorithms (GA) and experiential methods, such as case-based reasoning (CBR). A weakness in the GA is its reliance on limited mathematical models for …
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Probe request attack detection in wireless LANs using intelligent techniques
… STAs can associate (register) with the AP to gain full access to the network. Probe request and response management frames are unprotected, so the information is visible to sniffers. MAC addresses can be easily spoofed to bypass AP access lists. Probe requests can be sent by anyone with a …
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Production System Efficiency Optimization Using Hybrid AI Solution and Sensor Data
… Machine Learning (ML)-based simulation and Genetic Algorithms (GA). DEA is used to identify the efficient frontier of the production system based on historical or synthetic data. This data is used to train an ML model capable of simulating system behavior. GA is then applied to search for …
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Comprehensive optimization and practical design of power electronic systems under multiple competing performance demands
… by using stochastic search methods such as genetic algorithms (GA), and model simplification by linear regression. Two optimization schemes are proposed with different allocations of computational complexity, human expertise, and stochastic uncertainty. They provide flexibility for practical …
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Accelerating Structural Design and Optimization using Machine Learning
… the potential of DNN-based machine learning algorithms for accelerating the optimization of bio-inspired curvilinearly stiffened panels. But, the approach could have disadvantages for being only specific to similar structural design problems, and requiring large datasets for DNNs training. An …
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Stochastic Cellular Manufacturing System Design and Control
… Tremendous amount of work has been done regarding issues such as cell formation, cell loading and job scheduling. However, majority of literature lacks consideration of uncertainty in the problem definition phase, thus methodology. In this dissertation, the impact of uncertainty of demand, …
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Optimisation of hedging-integrated rule curves for reservoir operation
… This thesis presents the application of genetic algorithms (GA) for the optimisation of hedging-integrated reservoir rule curves. However, due to the challenge of establishing the boundary of feasible region in standard GA (SGA), a new development of the GA i.e. the dynamic GA (DGA), is …
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Adaptive scaling of evolvable systems
… of forms. A particular feature of models such as Genetic Algorithms (GA) [18, 12] is the incremental combination of partial solutions distributed within a population of solutions. This mechanism in principle allows certain problems to be solved which would not be amenable to a simple local search. …
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Automated Design of Multiphase Space Missions Using Hybrid Optimal Control
… system and obtains the required control history. Genetic algorithms (GA) and direct transcription with nonlinear programming (NLP) are introduced as methods of solution for the outer-loop and inner-loop problems, respectively. Automation of the inner-loop, continuous optimal control problem …
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