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 60 for “"self-organizing map"”.
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Learning manifolds with the Parametrized Self-Organizing Map and Unsupervised Kernel Regression
… that is specifically tuned to the Parametrized Self-Organizing Map (PSOM). The regularization approach makes it possible to deal with noisy or missing data in a principled manner, and it facilitates the construction of PSOMs from data that are not organized in a grid topology. In the second …
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An improved self organizing map using jaccard new measure for textual bugs data clustering
… the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. This research attempts a comparative analysis of both the clustering …
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Classification of Acoustic Emission Signals from an Aluminum Pressure Vessel Using a Self-Organizing Map
… was calculated for each waveform. A Kohonen self-organizing map (SOM) was used to cluster the spectra. The network clustered the data on a two-dimensional feature space according to the source of the signal. A total of 3,600 power spectra were used to train the neural network, and 1,800 were …
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Regulating Traffic Flow and Speed on Large Networks: Control and Geographical Self Organizing Map (Geo-SOM) Clustering
… on LA roads (not freeways). The geographical self organizing maps (GeoSOM) clustering algorithm is applied and tested on the LA network. The clustering goal is to identify a geographically connected region with small density variance. GeoSOM is able to achieve that objective with better …
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Prediction of Fatigue Life in 7075-T6 Aluminum from Neural Network Analysis of Acoustic Emission Data
… emission (AE) data acquisition system, a Kohonen self-organizing map, and a back-propagation neural network, AE data from 7075-T6 aluminum specimens were used to classify failure mechanisms and predict the number of fatigue cycles to failure. AE waveforms were captured from 40 notched tensile …
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Neural Network Fatigue Life Prediction in 7075-T6 Aluminum from Acoustic Emission Data
… data acquisition system coupled with a Kohonen self organizing map and a back propagation neural network were used to perform the analysis. AE waveforms were recorded during fatigue cycling of twenty-four notched 7075-T6 aluminum specimens using broad-band piezoelectric transducers. A Kohonen …
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Ultimate Compression After Impact Load Prediction in Graphite/Epoxy Coupons Using Neural Network and Multivariate Statistical Analyses
… damaged graphite/epoxy coupons using a Kohonen self-organizing map (SOM) neural network and multivariate statistical regression analysis (MSRA). An optimized use of these data treatment tools allowed the generation of a simple, physically understandable equation that predicts the ultimate …
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A SOM+ Diagnostic System for Network Intrusion Detection
… complex hybridization of a 3D full color Self-Organizing Map (SOM), Artificial Immune System Danger Theory (AISDT), and a Fuzzy Inference System (FIS). This SOM+ diagnostic archetype includes newly defined intrusion types to facilitate diagnostic analysis, a descriptive computational …
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Developmental model of sensorimotor map acquisition for a humanoid robot
… a novel method for acquiring a visuomotor mapping for hand-eye coordination. This model is trained on the iCub humanoid robot and used for smooth control of reaching. Applications of this model to sensorimotor associative learning are examined. In addition, a derivation of the …
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Ultimate Strength Prediction in Fiberglass/Epoxy Beams Subjected to Three-Point Bending Using Acoustic Emission and Neural Networks
… a 13 processing element hidden layer for mapping, and a single processing element output layer for predicting the ultimate load. The network, trained on seven beams, was able to predict ultimate loads in the remaining eight beams with a worst case error of +4.34 percent, which was within …
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Studying dialects to understand human language
… dialects using k-means clustering is done. Self-organizing maps are proposed as a tool for dialect research, and a self-organizing map is implemented for the purposes of testing this. Several areas for further research are identified, including how dialects are stored in the brain, more …
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Filtering of Acoustic Emission Data Through Principal Frequency Component Extraction
… network predictions and good classification in self-organizing map type neural networks applied to the testing data.</p>
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A collaborative, multi-agent based methodology for abnormal events management
… Three major data-driven approaches, namely, self-organizing map (SOM), principal components analysis (PCA), and kernel density estimator (KDE) were extended in this thesis to the domain of transient operations.
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Using emergent self-organizing maps to identify marine group II archaea genomic fragments from uncharacterized microbial metagenomic sequences
… II tetranucleotide signatures using emergent self-organizing maps was investigated. Fosmids from the HF200 library were chosen for sequencing based on end-sequence tetranucleotide clustering with group II seed sequences, as well as blastx homology. Fosmids were sequenced using a single 454- …
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Disambiguating words with self-organizing maps
… patterns by manipulating an accelerated Self-Organizing Map to save these example contexts and then references them to perform further context based disambiguation within the language. Through this process and after training on 125 examples, CLARIFY can now decipher that shrimp in the …
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Using Self-Organizing Maps for Computer Network Intrusion Detection
… others. For our study, we implemented our own self¬ organizing map (SOM), which we found to not be as heavily researched as other neural network approaches. Using the KDD Cup 99 dataset, we compared our own SOM implementation against other neural network implementations and determine the …
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Cross-domain self organizing maps
In this thesis, I present a method for organizing and relating events represented in two domains: the transition-space domain, which focuses on change and the trajectory-space domain, which focuses on movement along paths. Particular events are described in both domains, and each description is fed …
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Low Proof Load Prediction of Ultimate Strengths of Fiberglass/Epoxy I-Beams Using Acoustic Emission
… load for further analysis.</p> <p>A Kohonen self-organizing map was utilized to separate each individual data point (hit) into failure mechanism clusters. Then a multiple linear regression analysis was performed using the percentage of hits associated with each failure mechanism along with …
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Neural Network Detection of Fatigue Crack Growth in Riveted Joints Using Acoustic Emission
… a two-dimensional feature space using a Kohonen self organizing map (SOM). Then 132 crack growth and 137 rivet rubbing spectra were used to train a back-propagation neural network to provide automatic pattern classification. Although there was some overlap between the clusters mapped in the …
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Neural Network Fatigue Life Prediction in Notched Aluminum Specimens from Acoustic Emission Data
… and successfully classified using a Kohonen self-organizing map (SOM) to identify the plane stress and plane strain failure mode data. Furthermore, the early cycle (< 25% of fatigue life) AE amplitude distribution data from the test samples were used to predict fatigue lives using the BPNN. …
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