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 16 of 16 for “"Particle swarm optimization algorithm"”.
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Application of particle swarm optimization in adaptive self-interference cancellation
This thesis investigates the application of particle swarm optimization in self-interference cancellation. To achieve cancellation, the receiver has to differentiate between the transmit and receive signal. The transmit signal is already known at the transmitting side but it undergoes some …
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Optimization of microwave devices
This thesis deals with the optimization techniques for the improvement of the microwave devices performance. In particular, the technique proposed considers the Particle Swarm Optimization algorithm and applies such an algorithm to different devices. Different techniques are developed to connect …
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Design synthesis of NLMPC-based tracking controller for autonomous vehicles with active aerodynamic control
… framework with two layers: at the upper layer, a particle swarm optimization algorithm is used to find optimal solutions with desired trajectory-tracking performance; at the lower layer, a comprehensively coupled dynamic analysis is conducted among the three subsystems, including a nonlinear …
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Fuzzy Optimal Swarm of Autonomous Aircrafts for Target Determination and Convergence Control System
… project proposes analytical and theoretical algorithms for a networked swarm of autonomous vehicles, such as those used in planet exploration, and to be used in target location determination and convergence, an algorithm of this type could be used in an Autonomous Stratospheric Aircraft …
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Landscape Aware Algorithm Configuration
… if optimal performance is to be obtained from an algorithm on a specific problem or if a collection of algorithms are going to be compared in a fair manner. Unfortunately, adequately addressing the issue of parameter selection is time consuming and computationally expensive. Searching for …
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Clustering analysis using Swarm Intelligence
… thesis is concerned with the application of the swarm intelligence methods in clustering analysis of datasets. The main objectives of the thesis are ∙ Take the advantage of a novel evolutionary algorithm, called artificial bee colony, to improve the capability of K-means in finding global optimum …
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Learning an Artificial Neural Network (ANN) is an optimization task since it is desirable to find optimal weight sets of an ANN in the training process. Different equations are used to guide the network for providing an accurate result with less training and testing error. Most of the training …
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Enhanced Heat Transfer Performance by Shape Optimization of a Non-axisymmetric Droplet Evaporating on a Heated Micropillar
… <p>Enhanced Heat Transfer Performance by Shape Optimization of a Non-axisymmetric Droplet Evaporating on a Heated Micropillar</p> <p>By</p> <p>Haotian Wu</p> <p>Department of Mechanical Engineering and Materials Science</p> <p>Washington University in St. Louis, 2019</p> <p>Research Advisor: …
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Development of an autonomous radiation mapping robot
… presented. An integrated autonomous exploration algorithm, Particle Swarm Optimization algorithm, and the ability to accurately localize and map multiple radiation sources in both indoor and outdoor environments using actual sources are features of the system presented. Radiation maps provide an …
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Improved cuckoo search based neural network learning algorithms for data classification
… mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. These networks can be trained with gradient descent back propagation. The algorithm is not definite in finding the global minimum of …
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Observer-Based Simultaneous States and Parameters Estimation Method with Application to System Heath Monitoring
… system monitoring, fault diagnosis and the optimization of system control strategies. Provided in this thesis is a comprehensive review of the existing simultaneous states and parameters estimation techniques from the literature, discussing the strengths and limitation of each approach. As …
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Numerical simulation and optimisation of polymer flooding in a heterogenous reservoir : constrained versus unconstrained optimisation
… techniques (adjoint-based and a stochastic algorithm) to match data from a prolonged waterflood in the Watt Field, a semi-synthetic reservoir that contains a wide range of geological and interpretational uncertainties. Next, sensitivity studies were carried out to identify first-order …
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State Estimation in Active Distribution Systems: Comparison Between Weighted Least Squares and Extended Kalman Filter Algorithms
… Extended Kalman Filter (EKF) state estimation algorithms in active DNs. This dissertation develops and tests the performance of active distribution system state estimation WLS and EKF algorithms that consider the integration of DGs in standard IEEEbus test feeders. An important contribution of …
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Fuzzy time series analysis and prediction using swarm optimized hybrid model.
… combined fuzzy time series with the evolutionary algorithms, but the performance of the models is not quite satisfactory. In this research, a novel hybrid fuzzy time series forecasting model is proposed that used the historical data as the universe of discourse and the automatic clustering …
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Conceptual Design of Wind Farms Through Novel Multi-Objective Swarm Optimization
… role of land usage in wind farm layout optimization (WFLO); and (III) makes novel advancements on mixed-discrete particle swarm optimization algorithm through a multi-domain diversity preservation concept, to solve complex multi-objective optimization (MOO) problems.</p> <p>A …
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Electrochemical Model Based Fault Diagnosis of Lithium Ion Battery
A gradient free function optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized in parameter identification of the electrochemical model of a Lithium-Ion battery having a LiCoO2 chemistry. Battery electrochemical model parameters are subject to change under severe …