[PDF] Top 20 Self-organizing maps as an approach to exploring spatiotemporal diffusion patterns
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Self-organizing maps as an approach to exploring spatiotemporal diffusion patterns
... The mapping of both the complete dataset and of the individual waves was visualised in a GIS (Figure 5B and 5C). The results of the mapping for the complete time series, revealed that cluster 1 represents the medical ... See full document
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Classification of Engineering Consultancy Firms Using Self-Organizing Maps: A Scientific Approach
... Abstract — The present study analyzed consultants in Saudi Arabia. Engineering consultancy firms work on projects worth billions of US dollars annually in the fields of design and supervision. The quality of the services ... See full document
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Towards model evaluation and identification using Self Organizing Maps
... an approach using a Self-Organizing Map (SOM) to circumvent the identifiability problem induced by the low discrimina- tory power of aggregating performance ...a Self-Organizing Map is ... See full document
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Mapping model behaviour using Self Organizing Maps
... The main goal of this paper is to explore how the Herbst and Casper (2008) SOM-based approach can be improved by linking it to the Signature Index concept (Gupta et al., 2008), which defines the similarity between ... See full document
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Data Clustering and Topology Preservation Using 3D Visualization of Self Organizing Maps
... From the results in Figure 5 too, the quantization errors and topographic errors in 3D-SOM behaved the similar way with those in 2D-SOM. It seems that as in 2D-SOM, the higher number of output neurons has also ... See full document
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Intelligent Computational Modeling and Prediction of Coliform Growth in Tropical Lakes based on Hybrid Self Organizing Maps (SOM) and Fuzzy Logic Approaches
... The approach outlined in this paper using the hybrid approaches of SOM and Fuzzy Logic to perform water quality modeling and Coliform prediction of tropical lakes and wetlands of Putrajaya could be a better ... See full document
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Self Organizing Maps for the Visual Analysis of Pitch Contours
... between L1 and L2 performance despite the dif- ferent characteristics of the two experimental data sets. We visualizaed and animated the SOM train- ing phase and presented this to the researcher as well. This may seem ... See full document
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Wave extreme characterization using self-organizing maps
... dissimilarity algorithm (MDA) in order to reduce the redun- dancies of the frequent low and moderate sea states, as done by Camus et al. (2011a). Indeed, MDA is a technique that reduces the density of inputs by ... See full document
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Hidden Markov Models and Self Organizing Maps Applied to Stroke Incidence
... new approach based on Hidden Markov Models (HMMs) and self-organizing maps (SOM), interpreting the back- ground from the viewpoint of weather ...weather patterns that would serve as ... See full document
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Molecular subtyping of bladder cancer using Kohonen self-organizing maps
... HPV DNA (P < 0.004), Chromosome 9 (P = 0.04) and the A148T polymorphism (rs 3731249) in CDKN2A (P = 0.02) were associated with progression following treatment. Multivariable analysis of these parameters identified ... See full document
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A Framework for Face Recognition using Self Organizing Map (SOM) and Soft k-NN Ensemble
... alternate approach of representing the face topological space with self-organizing maps (SOMs) ...this approach, the compact and sturdy illustration of the topological space may be ... See full document
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Space-in-time and time-in-space self-organizing maps for exploring spatiotemporal patterns
... We ran SOM with the following parameters: matrix size 5x3, 300,000 iterations, learning radius 2, learning rate 0.02. The resulting space-in-time SOM matrix is shown in Figure 3. As mentioned before, cell colors in a SOM ... See full document
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A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage
... the Self-Organizing Map (SOM) method, which groups objects and arranges them according to similarity of relevant data ...SOM approach to spatial situations and to local temporal variations and obtain ... See full document
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A Self-Organizing Diffusion Mobile Adaptive Network for Pursuing a Target
... steps, diffusion algorithms can be categorized into two classes known as the Combine-then-Adapt and Adapt-then-Combine ...of diffusion LMS outperforms the CTA algorithm [16]. The initial diffusion ... See full document
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Catchment classification by runoff behaviour with self organizing maps (SOM)
... of patterns in observed data is almost non- existent (McDonnell and Woods, 2004; Woods, ...that maps each attribute set x to one of the predefined class labels y (Tan et ... See full document
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Musical Note Extraction using Self Organizing Feature Maps
... The choice of Artificial Neural Networks as a method for identification of musical notes is justified by the human analogy. Music, whether be it for listening, enjoying, composing or understanding, is considered to be ... See full document
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Modeling Directional Selectivity Using Self-Organizing Delay-Aadaptation Maps
... [r] ... See full document
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Distributed Range Free Localization Algorithm Based on Self Organizing Maps
... In Mobile Ad Hoc Networks (MANETs), determining the physical location of nodes (localization) is very important for many network services and protocols. This paper proposes a new Distributed Range-Free Localization ... See full document
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EFFICIENT IMAGE COMPRESSION TECHNIQUE USING SELF ORGANIZING FEATURE MAPS
... Kohonen’s Self Organizing Feature Map and the Entropy Coding of the indexes obtained after SOFM ...technique. Self Organizing Feature Maps and Entropy Coding have been discussed in this ... See full document
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Monitoring industrial hydrogenation of soybean oil using self-organizing maps
... with self-organizing maps (SOM) may be an alternative to extract relevant information during the ...weight maps depicted the variation of monounsaturated fatty acids associated with the ... See full document
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