Results 11 to 20 of about 7,151,068 (329)
The Parameterless Self-Organizing Map Algorithm [PDF]
IEEE Transactions on Neural Networks, 2006 The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM ...
Berglund, Erik, Sitte, Joaquin
openaire +7 more sources
Genome signatures, self-organizing maps and higher order phylogenies: a parametric analysis [PDF]
, 2007 Genome signatures are data vectors derived from the compositional statistics of DNA. The self-organizing map (SOM) is a neural network method for the conceptualisation of relationships within complex data, such as genome signatures.
Gatherer, Derek
core +10 more sources
Self-Organizing Map Convergence
International Journal of Service Science, Management, Engineering, and Technology, 2018 Self-organizing maps are artificial neural networks designed for unsupervised machine learning. Here in this article, the authors introduce a new quality measure called the convergence index. The convergence index is a linear combination of map embedding
Robert Tatoian, L. Hamel
semanticscholar +4 more sources
Randomized Self-Organizing Map [PDF]
Neural Computation, 2021 We propose a variation of the self-organizing map algorithm by considering the random placement of neurons on a two-dimensional manifold, following a blue noise distribution from which various topologies can be derived. These topologies possess random (but controllable) discontinuities that allow for a more flexible self-organization, especially with ...
Nicolas P. Rougier +1 more
openaire +5 more sources
Adaptive Self-Organizing Map Using Optimal Control
Mathematics, 2023 The self-organizing map (SOM), which is a type of artificial neural network (ANN), was formulated as an optimal control problem. Its objective function is to minimize the mean quantization error, and the state equation is the weight updating equation of ...
Ali Najem Alkawaz +6 more
doaj +1 more source
A self-organizing map approach for constrained multi-objective optimization problems
Complex & Intelligent Systems, 2022 There exist many multi-objective optimization problems (MOPs) containing several inequality and equality constraints in practical applications, which are known as CMOPs.
Chao He +6 more
semanticscholar +1 more source
SERVICE DESIGN WITH MACHINE LEARNING BASED ON USER ACTION HISTORY [PDF]
Acta Electrotechnica et Informatica, 2020 With the development of IoT techniques, it become easier to collect users’ action data. By analyzing and using those data, consumers and producers will mutually exchange their intelligence and better customize product development processes.
Xinyue WANG +3 more
doaj +1 more source
CLUSTERING PERKEMBANGAN KASUS COVID-19 DI INDONESIA MENGGUNAKAN SELF ORGANIZING MAP
Jurnal Dialektika Informatika, 2020 Tujuan dari penelitian ini adalah melakukan pengelompokan daerah-daerah di Indonesia berdasarkan perkembangan kasus Covid-19. Pada penelitian ini digunakan Jaringan Syaraf Tiruan Kohonen yang disebut juga Self Organizing Map (SOM).
Tutik Khotimah, Darsin
doaj +1 more source
Rough Self Organizing Map [PDF]
Applied Intelligence, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sankar K. Pal +2 more
openaire +1 more source
Signal Self Organizing Map [PDF]
2007 International Joint Conference on Neural Networks, 2007 The self organizing map (SOM) has been applied to wide ranges of fields including computer vision and image processing. Despite of its simple training algorithm, the vectorial input pattern of SOMs induced a sequence of drawbacks which should not be overlooked.
Chi Kin Chow 0001, Shiu Yin Yuen
openaire +2 more sources