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 85 for “"Multilayer perceptron"”.
-
Tone classification of syllable -segmented Thai speech based on multilayer perceptron
… were used as the main discriminating features. A multilayer perceptron (MLP) trained by backpropagation method was employed to classify these features. The proposed system was evaluated on 920 test utterances spoken by five male and three female Thai speakers who also uttered the training speech. …
-
An improved multilayer perceptron based on wavelet approach for physical time series prediction
… an idea to develop a model called An Improved Multilayer Perceptron based on Wavelet Approach for Physical Time Series Prediction (W�MLP) to overcome such drawbacks of ordinary NN. W-MLP, a network model with a wavelet technique added in the network, is trained using the standard …
-
An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
… for training ANN, namely the widely used Multilayer Perceptron (MLP). Here, three improved learning approaches inspired by artificial honey bee's behavior are used to train MLP. They are: Global Guided Artificial Bee Colony (GGABC), Improved Gbest Guided Artificial Bee Colony (IGGABC) and …
-
Novel ECG analysis with application to atrial fibrillation detection
… are designed which are the Cascade Hybrid Multilayer Perceptron (CHMLP) and the Multi-Classify Hybrid Multilayer Perceptron (MCHMLP) networks which improved version of Hybrid Multilayer Perceptron (HMLP) neural network.The MCHMLP network performs a multiple classification by doing the …
-
Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
… the proposed fully tuned RBF was compared with Multilayer Perceptron (MLP), Hybrid Multilayer Perceptron (HMLP) and RBF networks trained with CT algorithm. The findings indicated that the fully tuned RBF with minimal resource allocating networks (MRAN) automatically selected seven neurons with …
-
Identification of shift variation in bivariate process using pattern recognition technique
… in this study: (i) Statistical Features-Multilayer Perceptron (SF-MLP) and (ii) Integrated Multivariate Exponentially Weighted Moving Average-Multilayer Perceptron (MEWMA-MLP). Input representation for the MLP recogniser in both schemes was designed based on summary statistical features …
-
Higher order neural networks for financial time series prediction
… Neural Network were used, as well as the Multilayer Perceptron. Furthermore, a novel neural network architecture which comprises of a feedback connection in addition to the feedforward Ridge Polynomial Neural Network was constructed. The proposed network combines the properties of both …
-
Deep CNN and MLP-based vision systems for algae detection in automatic inspection of underwater pipelines
Artificial neural networks, such as the multilayer perceptron (MLP), have been increasingly employed in various applications. Recently, deep neural networks, specially convolutional neural networks (CNN), have received considerable attention due to their ability to extract and represent high-level …
-
Neural bus networks
… from Boston buses. Three models are trained: multilayer perceptron, convolutional neural network and recurrent neural network. Recurrent neural networks show the best performance when compared to feed forward models. This indicates that neural time series models are effective at modeling bus …
-
DEVELOPMENT AND APPLICATIONS OF MACHINE/DEEP LEARNING TECHNIQUES IN FLUID DYNAMICS
… fluid flow problems. Firstly, the conventional multilayer perceptron (MLP) networks are enhanced by the Gaussian radial basis function (RBF) with trainable centers and widths. Activated by Gaussian RBFs, the proposed MLP-RBF network is more accurate and efficient in nonlinear regression …
-
High Dimensional Analysis of Genetic Data for the Classification of Type 2 Diabetes Using Advanced Machine Learning Algorithms
… deep learning stacked autoencoders, and a multilayer perceptron for classification. Quality control procedures are conducted to exclude genetic variants and individuals that do not meet a pre-specified criterion. Logistic association analysis under an additive genetic model adjusted for …
-
A generalised feedforward neural network architecture and its applications to classification and regression
… as subsets both SIANN and the conventional Multilayer Perceptron (MLP) architectures. The original SIANN structure has the number of shunting neurons in the hidden layers equal to the number of inputs, due to the neuron model that is used having a single direct excitatory input. This was …
-
Improvements and augmentations to Learning Based Java: a Java based learning based programming language
… 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.
-
Inductive logic programming with gradient descent for supervised binary classification
… a 71.7% accuracy, which is comparable to multilayer perceptron and randomized forest models. We conclude by suggesting directions for future applications and potential improvements.
-
Machine Learning techniques to discover and understand the population of flare stars in MeerLICHT data
… curve. We train random forest (sect 4.1.1) and multilayer perceptron neural network (sect 4.1.3) models on simulated LSST PLAsTiCC data and real data from the MeerLICHT survey. We found that the random forest model outperforms the neural network model in both data sets, achieving test accuracy …
-
Αξιολόγηση επίδοσης του τραπεζικού μάνατζμεντ μέσω της μέτρησης της πιστοληπτικής ικανότητας των δανειοδοτούμενων μικρομεσαίων επιχειρήσεων (SMEs) με τη χρήση μοντέλων credit scoring, κατά τη διάρκεια της κρίσης
… δένδρα αποφάσεων, νευρωνικό δίκτυο “Multilayer perceptron” και νευρωνικό δίκτυο “Radial Basis Function”. Από τη μελέτη μας προκύπτει ότι το αποτελεσματικότερο μοντέλο είναι το νευρωνικό δίκτυο “Multilayer perceptron”, ενώ ακολουθούν η διωνυμική λογαριθμική παλινδρόμηση και τα δένδρα …
-
Disruption prediction at JET [Joint European Torus]
… The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as ?i and q? with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. …
-
Analysis of alternative methods for long-term wind speed and initial site assessment for purposes of wind energy production estimation
… than linear regression in absolute terms. The multilayer perceptron (MLP) artificial neural network (ANN) also exhibited promise in dealing with some of the non-linear aspects of the data sets, although its accuracy was found to be worse than linear regression by 0.79% in absolute terms. The …
-
How negative sampling provides class balance to rare event case data using a vehicular accident prediction project as a use case scenario
… Additionally, two types of predictive models, a Multilayer Perceptron and a Logistic Regression model, are created and directly compared in terms of predictive capability. Ultimately, the best model for predictive performance is heavily dependent on the specific implementation and desired results.
Page 1 of 5