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 97 for “"Multi-layer perceptron"”.
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Sonic Analysis for Machine Learning: Multi-Layer Perceptron Training using Spectrograms
… of visualising the weights inside neural network layers – matrices of variables containing the data that determines what information the network has learned – for better understanding of training and trouble-shooting of such networks that have been trained to classify images. This approach spawned …
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Investigation of a multi-layer perceptron network to model and control a non-linear system.
… a non-linear process. The scheme is based on a Multi-Layer Perceptron neural net-work as a modelling tool for a real non-linear, dual tank, liquid level process. A neural network process model is developed and evaluated firstly in simulation studies and then subsequently on the real process. …
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The impact of architecture on the performance of artificial neural networks
… paid to the impact on the performance of the multi-layer perceptron of architectural issues, and the use of various strategies to attain an optimal network structure. However, there are still perceived limitations with the multi-layer perceptron and networks that employ a different …
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Nonlinear Controller Design and Implementation for a Magnetic Levitation System
… neural networks (ANNs). Two neural networks, the multi-layer perceptron (MLP) and the single multiplicative neuron (SMN), are investigated in this work. A novel form of ANN, namely, single multiplicative neuron (SMN), is proposed in place of the more traditional multi-layer perceptron (MLP). SMN …
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Detection and Analysis of Molten Aluminium Cleanliness Using a Pulsed Ultrasound System
… logistic regression, support vector machine, multi-layer perceptron and a radial basis function network. The hyperparameters are tuned using 10- fold repeated cross-validation. The multi-layer perceptron offers the best performance in all cases. For determining the quality outcome of a cast …
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Analysing fuel transactions of government vehicles in the Eastern Cape, South Africa
… Predictive models, including XGBoost, Multi-layer Perceptron, and Random Forest, are employed to automate the classification of transactions based on these fraud indicators. The Multi-layer Perceptron demonstrates the best performance, achieving an accuracy of 87% on the test set. The …
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Application of neural network techniques for modeling of blast furnace parameters
… in a blast furnace. It compares the ability of multi-layer perceptron neural networks for prediction with other blast furnace prediction techniques. The output variables: Hot Metal Temperature, Silicon Content, Slag Basicity, RDI, and +10 are all modeled using the MLP networks. Different …
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Evaluation of a multi variated analysis for the selection of t-tbar multijet events in the current CMS implemented environment at LHC
In the present study we are using multi variate analysis techniques to discriminate signal from background in the fully hadronic decay channel of ttbar events. We give a brief introduction to the role of the Top quark in the standard model and a general description of the CMS Experiment at LHC. We …
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Machine learning for time series anomaly detection
… then that point was flagged as anomalous. I used multiple models such as Long Short-Term Memory (LSTM), autoregression, Multi-Layer Perceptron, and Encoder-Decoder LSTM. I used the "Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding" paper as a basis for my analysis, …
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Evaluating Modern Neural Network Architectures for Suicide Prediction
… research aims to evaluate the capabilities of Multi-Layer Perceptron (MLP) and a selection of its successors, ResNet and MLP with a category embedding layer, at the task of predicting suicidal ideation among high-school students. This research finds ResNet to be the most capable at minimizing …
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Forecasting and modelling the VIX using Neural Networks
… In particular, we focus on the performance of Multi-layer Perceptron (MLP) and the Long Short Term (LSTM) Neural Networks in predicting the CBOE Volatility Index (VIX). The inputs into these models includes the VIX, GARCH(1,1) fitted values and various financial and macroeconomic explanatory …
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Simulating Urban Landscape Transformation: Implications for Urban Wetlands at Multiple Scales
… SPOT satellite images of Kansas City using multi-layer perceptron neural network and maximum likelihood classification techniques. The impact of these two classification methods on the overall accuracy of land change prediction was assessed. The study made use of the classified map of a …
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Project dispute resolution satisfaction of construction clients in Hong Kong
… the classification and prediction ability of the multivariate discriminant analysis and artificial neural network multi-layer perceptron modeling. Both techniques were employed in this research for the identification of critical variables and the model development. The verification of the critical …
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The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions
… non-localised basis (non-linear) functions (Multi-layer Perceptron) versus those employing localised basis functions (Radial Basis Function Network).
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A time-delayed neural network approach to the prediction of the hot metal temperature in a blast furnace
… already done by the group on this data using a multi-layer perceptron (MLP). This paper examines the architectures used in detail and then presents the results obtained. A survey of the data mining field related to TDNNs is also included. This survey consists of the theoretical background …
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A functional link neural network with modified cuckoo search for prediction tasks
… changes. Neural network, especially the Multi-Layer Perceptron (MLP) which uses Back Propagation algorithm (BP) as a supervised learning method, has been successfully applied in various problems for meteorological prediction tasks. However, this architecture has still been facing problems …
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On-device mobile speech recognition
… further within the thesis. Secondly, a dynamic Multi-Layer Perceptron approach is developed. This builds on the drawbacks of the ESN and provides a dynamic way of handling speech signal length variabilities within its architecture. This novel Dynamic Multi-Layer Perceptron uses both the Linear …
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Intrusion detection for industrial control systems
… forward artificial neural network known as a Multi-Layer Perceptron (MLP), was implemented for comparison due to its ease of reuse for running in a production environment. The experimental results show that both kNN and MLPs are effective approaches for identifying malicious network traffic; …
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Secure analog-to-digital conversion against power side-channel attack
… SAR ADC PSA methods based on multi-layer perceptron net-works (MLP-PSA) and convolutional neural networks (CNN-PSA). When applied to a SAR ADC without PSA protection, the proposed attack methods decode the power supply current waveforms of the SAR ADC into the corresponding A/D …
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Anomaly detection in semiconductor manufacturing through time series forecasting using neural networks
… to the anomaly detection problem. With multiple recipes and multivariate data, it is difficult for engineers to reliably detect anomalies in the manufacturing process. An experimental study into anomaly detection through time series forecasting is carried out with application to a plasma …
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