The self-organising map
Combining a self organising map with memory based learning
... For this reason there has been some interest in various forms of memory editing whereby some method of selecting a subset of the memory base is employed to reduce the number of comparisons. This paper investigates the ...
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Fault Detection in the Activated Sludge Process using the Kohonen Self-Organising Map
... can successfully be determined by incorporating estimation techniques. However, the challenge with these approaches is that they require robust models to represent the plant under various conditions including fault ...
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Multiple 2D self organising map network for surface reconstruction of 3D unstructured data
... that Self Organising Map (SOM) model, the conventional surface approximation approach with Non Uniform Rational B-Splines (NURBS) surfaces, and optimisation methods such as Genetic Algorithm (GA), ...
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Self-Organising Map Approach to Individual Profiles: Age, Sex and Culture in Internet Dating
... Keywords: Self-Organising Map; Neural Network; Complex Data; Internet Dating; Age; Sex; Culture; Relationship; Visualisation Background 1.1 The notion that we live in a networked society has become ...
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Self organising map machine learning approach to pattern recognition for protein secondary structures and robotic limb control
... a self- organising map structure-fitting methodology named second- ary structure neural network (SSNN) to aid this process and reduce the level of expertise ...a map, and SSNN2 creates a ...
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Extending the Kohonen Self-Organising Map by Use of Adaptive Parameters and Temporal Neurons
... From Figure 4.8(a), we can see th a t at 5000 epochs, 39/64 sequences were clas sified. By 8000 epochs, this has dropped to 14/64. W ith regards to the TKM , th e neighbourhood cannot be allowed to tend to a small size ...
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Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning
... The study was developed using the data from the PSICOST projects entitled ‘ Development of a health map of services and facilities for the integral care of people with mental illness and[r] ...
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Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications
... Network-Self-Organizing Map for data clustering of marine engine condition monitoring applications Condition monitoring is the process of monitoring parameters expressing machinery condition, interpreting ...
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Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications
... Condition monitoring is the process of monitoring parameters expressing machinery condition, interpreting them for the identification of change which could be indicative of developing faults. Data pre-processing and ...
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Classification of Cardiac Arrhythmia using Hybrid Technology of Fast Discrete Stockwell-Transform (FDST) and Self Organising Map
... unique self-organizing maps (SOMs) based neural network for classification of arrhythmia according to a particular ECG signal, the generation of SOMs is based on the certain unique signatures of ECG signals and ...
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Visualising Class Distribution on Self-Organising Maps
... 2 Self-Organising Map The SOM is a neural network model for unsupervised ...the map is assigned a weight vector, which is of the same dimensionality as the vectors in the input ...the ...
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Self organising maps for visualising and modelling
... There are a number of ways of determining signifi- cance. One way [55] is to reform the map many times, from different random starting points. A factor that is significant will remain significant (or a “ positive ...
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Unsupervised Learning and Self Organising Networks
... and Self Organising Networks Unsupervised learning is one of the three forms of machine learning; supervised, unsupervised, and reinforcement ...to map inputs to the label plant or ...
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Self-Organising and Self-Learning Model for Soybean Yield Prediction
... In this paper, the ALMMo-1 system is implemented to predict soybean crop yields from factors that affect the yield. The model achieves high accuracy. Distinctive characteristics of the model are the interpretability and ...
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Self Organising Maps for Anatomical Joint Constraint
... Keywords-Self Organizing Map; Unit quaternion; Constraint; Neural Network I. I NTRODUCTION Joint systems are important constituents of anatomical models, they are used in simulation to retain anatomically ...
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Self-organising management of user-generated data and knowledge
... The survey of these applications is shown in Table 2 ( ‘Commercial applications’ section). In both cases a central governance is used. The companies control any changes to policies governing the data they hold and access ...
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Survey on Supervised Classification using Self Organising Maps
... Keywords— SOM, SOM-KS, hit map, saliency map, colour space , entropy index. I. I NTRODUCTION Image classification refers to the task of extracting information classes from a multiband raster image. The ...
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Introduction Hebbian learning Generalised Hebbian learning algorithm Competitive learning Self Self-organising computational map: organising computational map: Kohonen network Summary
... can be activated simultaneously, in competitive learning, only a single output neuron is active at learning, only a single output neuron is active at.. Competitive learning Competitive[r] ...
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Self-Organising Data Mining
... 2. Self-organising data mining (SODM) In contrast to Neural Networks that use Genetic Algorithms as an external procedure to optimise the network architecture and several pruning techniques to counteract ...
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A Self-Organising Model of Thermoregulatory Huddling
... a self-organising system, because complex properties of the collective group behaviour are thought to emerge spontaneously through simple interactions between ...a self-organising system, and ...
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