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.
Results
Showing 1 to 20 of 65 for “"neural network (NN)"”.
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Modeling and control of friction stir welding
… of this study were twofold. First, a discrete neural network (NN) based adaptive controller was developed and implemented on a six-axis robotic FSW machine...Second, the effect of process parameters and tool design was studied utilizing various sensor measurements"--Abstract, page iv.
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Hardware Implementation of a Novel Image Compression Algorithm
… transform coding, vector quantization and neural networks. In this thesis, a novel adaptive compression technique is introduced based on adaptive rather than fixed transforms for image compression. The proposed technique is similar to Neural Network (NN)-based image compression and its …
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Modeling of Hysteretic Behavior of Beam -Column Connections Based on Self -Learning Simulation
In this research, a new neural network (NN) based cyclic material model is applied to inelastic hysteretic behavior of connections. In the proposed model, two energy-based internal variables are introduced to expedite the learning of hysteretic behavior of materials or structural components. The …
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Application of statistical learning theory to plankton image analysis
… a traditional learning vector quantization (LVQ) neural network (NN) classifier built on shape-based features and different pattern representation methods, I developed a classification system combined multi-scale cooccurrence matrices feature with support vector machine classifier. This new method …
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Optimising credit card fraud detection through machine learning and deep learning with spatial-temporal imbalance handling
… and anomaly detection. We devised an innovative methodology using sophisticated machine learning (ML) and deep learning (DL) approaches in conjunction with data balancing techniques, including random over sampling (ROS), synthetic minority over-sampling technique (SMOTE), adaptive …
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Improvements and augmentations to Learning Based Java: a Java based learning based programming language
… generated datasets. Moreover, we introduce Neural Network (NN), in particular, Multilayer Perceptron (MLP), to LBJava. We also did some miscellaneous work. Lastly, we conclude on all the extended and added components and provide recommendations for future work.
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Comparison of Some Statistical and Machine Learning Models for Continuous Survival Analysis
… Cox, Survival Trees, Random Survival Forest, and Neural Networks. Model performance was evaluated using Integrated Brier score (IBS), Area Under the Curve and Concordance index. Our findings shows consistent dominance of Neural Network (NN) and Random Survival Forest (RSF) models across multiple …
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Data-driven Estimation of Low-Power Long-Range Signal Parameters by an Unauthenticated Agent using Software Radio
… information over low- power communication networks. In such scenarios, agents communicate intermittently with each other, often with limited power and over unlicensed spectrum bands that are susceptible to interference, eavesdropping, and Denial-of-Service (DoS) attacks. In this work, we …
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FAULT DETECTION AND ISOLATION FOR WIND TURBINE DYNAMIC SYSTEMS
… faults are successfully detected. In addition, a neural network (NN) method is proposed for WTS fault detection and isolation. Two radial basis function (RBF) networks are employed in this method. The first NN is used to generate the residual from system input/output data. A second NN is used as a …
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Time-efficient offloading and execution of machine learning tasks between embedded systems and fog nodes
… be used efficiently. One such technology is the Neural Network (NN). NN's, combined with the Internet of Things (IoT), can utilize the massive amounts of data produced to optimize, control, and automate embedded systems, giving them more functionality than ever before. However, the status quo of …
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Complex Vehicle Modeling: A Data Driven Approach
This thesis proposes an artificial neural network (NN) model to predict fuel consumption in heavy vehicles. The model uses predictors derived from vehicle speed, mass, and road grade. These variables are readily available from telematics devices that are becoming an integral part of connected …
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Fault tolerant control for nonlinear aircraft based on feedback linearization
… provide further robust control performance:- A neural network (NN)-based adaption mechanism is used to develop reconfigurable FTFC performance through the combination of a concurrent updated learninglaw. - The combined feedback linearization and NN adaptor FTFC system is further improved through …
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A neural network model for resource leveling
A new neural network model aimed at solving the resource leveling (RL) problem in construction is developed. The model is derived by mapping a formulation of the RL problem as a quadratic augmented Lagrangian multiplier (QALM) optimization, onto an artificial neural network (ANN) architecture …
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Development of a hybrid intelligent system for on-line real-time monitoring of nuclear power plant operations
… operation of the NPPs, when their malfunctions cannot be detected in a timely manner. The lost availability can result in millions of dollars economic loss. Currently, one of the main reasons of the incapacity for avoiding such critical system failures is the lack of an appropriate health …
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Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
A quadcopter is a four-rotor unmanned aerial vehicle (UAV) with nonlinear and strongly coupled dynamics system. A precise dynamics model is important for developing a robust controller for a quadcopter. NN model capable to obtain the accurate dynamics model from actual data without having any …
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Collaborative system and multi robots based on pneumatic muscle actuator
… is proposed by using a parallel structure of the neural network NN and proportional P controller (PNNP controller). The presented continuum arms formed a multiple robot system to perform several tasks under the PNNP controller.
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Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems
… implemented with an Adaptive Critic (AC) based neural network (NN) structure has evolved as a powerful technique for solving the Hamilton-Jacobi-Bellman (HJB) equations. As interest in ADP and the AC solutions are escalating with time, there is a dire need to consider possible enabling factors …
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Human action recognition with 3D convolutional neural networks
Convolutional neural networks (CNNs) adapt the regular fully-connected neural network (NN) algorithm to facilitate image classification. Recently, CNNs have been demonstrated to provide superior performance across numerous image classification databases including large natural images (Krizhevsky et …
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Design and implementation of a novel lightweight soft upper limb exoskeleton using pneumatic actuator muscles
… Derivative) PID controller as an input for MRAC. Neural Network (NN) is also used in MRAC to improve the performance of MRAC.
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Automated Process Planning for Five-Axis Point Milling of Sculptured Surfaces
… efforts for building an automated process planning system for 5-axis point milling of sculpture surfaces (finish cut) are presented. Based on existing research, workflow for process planning was carefully planned out, with optimization and improvements in the following areas: Firstly, a new …
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