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 52 for “"multi-layer perceptron (MLP)"”.
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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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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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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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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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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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Development of an Automated Coin Grading System: Integrating Image Preprocessing, Feature Extraction, and ML Modeling
… reverse sides of the coins are processed using a multi-layer perceptron (MLP) model and a random forest model. The best-performing model is then selected to grade the coins by analyzing their overall wear patterns and color characteristics. Our grading system has demonstrated an accuracy of up to …
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GOES-R Supervised Machine Learning
… various properties. In this project we explore a multi-layer perceptron (MLP), neural network, to train a model using various sample size. We compare our R-square scores, mean square error (MSE), and mean absolute (MAE) between pCal and MLP models. In addition, we explore different artificial …
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A novel approach to determine building occupancy for cooling energy consumption prediction
… and require a longer computational time. Multi-layer perceptron (MLP) model of artificial neural network (ANN) is adopted in this thesis. The model is widely used in engineering approaches that render good performance in adaptability, nonlinearity and mapping. It also has good ability in …
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A comparative evaluation of machine learning models for stock price prediction and uncertainity estimation
… Random Forest (RF), Gradient Boosting (GB), Multi-Layer Perceptron (MLP), and a hybrid stacking ensemble composed of multiple base learners. For uncertainty quantification, three interval prediction methods were used: Bootstrap Residuals, Quantile Regression Forests (QRF), and Conformalised …
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Hybride Modellbildung zur Prozessführung von Fed-Batch-Kultivierungen mit Aspergillus niger
… a combination of a mechanistic model part and a multi-layer perceptron (MLP) as black box part. In the second part, a structured biological model for A.niger is derived, which also includes online measurement data and can therefore be used for process control. In this model, the product formation …
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
… has been a dynamic area of research, with the Multi-Layer Perceptron (MLP) trained with back propagation (BP) mostly worked on by various researchers. However, this algorithm is prone to have difficulties such as local minimum which are caused by neuron saturation in the hidden layer. Most …
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Prediction of Enrollment using Computational Intelligence
… model. A novel form of ANN, namely, single multiplicative neuron (SMN), as an alternative to traditional multi-layer perceptron (MLP), has been used for time series prediction. A variation of population based heuristic optimization approach, namely, co-operative particle swarm optimization …
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Deep Reinforcement Learning for Multirotor Flight Control: A Comparative Study of Sim-to-Real Training and Real-World Performance
… Learning (DRL) for low-level flight control of multirotor unmanned aerial vehicles (UAVs), focusing on factors that most influence sim-to-real policy transfer. Using the Proximal Policy Optimization (PPO) algorithm, extensive ablation studies evaluated the effects of domain randomization, reward …
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Classification of Malicious Web Traffic
… different features. The data were divided into multiple vulnerability scans and attack classes. Five batch supervised machine learning algorithms (J48, PART, Support Vector Machine SVM, Multi Layer Perceptron MLP and Naive Bayes Learner NB) and one stream semi-supervised algorithm (CSL-Stream) …
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Energy-Efficient Neural Network Hardware Design and Circuit Techniques to Enhance Hardware Security
… time-domain computing scheme for fully connected multi-layer perceptron (MLP) neural network and the other is an efficient binarized architecture for long short-term memory (LSTM) neural network. Secondly, to enhance the hardware security and ensure secure data communication between edge devices, …
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New methods for the protection of embedded generators against the loss of utility networks.
… solution. Further research indicated that the Multi-Layer Perceptron (MLP) with back-propagation learning had been used in many power systems control and protection applications. Its ability to recognise and classify complex input patterns made it very suitable for the LOM application. …
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Automatic solar feature detection using image processing and pattern recognition techniques
… advanced pattern recognition techniques such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) are used. By tracking the entire process of flares, the motion properties of two-ribbon flares are derived automatically. In the applications of the solar …
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Intelligent Neural Network Control System Design and FPGA Based Implementation
… In this study, the effectiveness of single multiplicative neuron (SMN) in place of traditional multi-layer perceptron (MLP) is investigated. The objectives were to (i) verify the feasibility of SMN based control systems, (ii) quantitatively compare the performance of SMN and MLP based …
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