Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Neural self-organizing

Previous work in our group had shown the power of self-organizing neural networks for the projection of high-dimensional datasets into two dimensions while preserving clusters present in the high-dimensional space even after projection [27]. In effect, 2D maps of the high-dimensional data are obtained that can show clusters of similar objects. [Pg.193]

This format was developed in our group and is used fruitfully in SONNIA, software for producing Kohonen Self Organizing Maps (KSOM) and Coimter-Propaga-tion (CPG) neural networks for chemical application [6]. This file format is ASCII-based, contains the entire information about patterns and usually comes with the extension "dat . [Pg.209]

Now, one may ask, what if we are going to use Feed-Forward Neural Networks with the Back-Propagation learning rule Then, obviously, SVD can be used as a data transformation technique. PCA and SVD are often used as synonyms. Below we shall use PCA in the classical context and SVD in the case when it is applied to the data matrix before training any neural network, i.e., Kohonen s Self-Organizing Maps, or Counter-Propagation Neural Networks. [Pg.217]

Kohonen networks, also known as self-organizing maps (SOMs), belong to the large group of methods called artificial neural networks. Artificial neural networks (ANNs) are techniques which process information in a way that is motivated by the functionality of biological nervous systems. For a more detailed description see Section 9.5. [Pg.441]

Tools SONNIA [12] (Self-Organizing Neural Network for Information Analysis)... [Pg.461]

SONNIA is a self-organizing neural network for data analysis and visualization. [Pg.461]

SONNIA (Self Organizing Neural Network for Information Analysis), http //uww2.chende.uni-eTiangen.de/ softwarefkmap/ and http //www.mol-net.de/... [Pg.484]

Figure 10.1-4. Distribution of compounds from two data sets in the same KNN (Kohonen s self-organizing neural network) map by using 18 topological descriptors as input descriptors, where 1 represents the 1588 compounds in the Merck data set (excluding those compounds that are also in the Huuskonen data set) 2 represents the 799 compounds in the Huuskonen data set (excluding those compounds that are also in the Merck data set), and 3 represents the overlapping part of the Huuskonen data set and the Merck data set. Figure 10.1-4. Distribution of compounds from two data sets in the same KNN (Kohonen s self-organizing neural network) map by using 18 topological descriptors as input descriptors, where 1 represents the 1588 compounds in the Merck data set (excluding those compounds that are also in the Huuskonen data set) 2 represents the 799 compounds in the Huuskonen data set (excluding those compounds that are also in the Merck data set), and 3 represents the overlapping part of the Huuskonen data set and the Merck data set.
Til most cases, only one of the two regioisomers is preferentially formed. Wc will show here how reaction classification by a self-organizing neural network can be used for the prediction of the preferred regioisomer in a pyrazole synthesis. [Pg.545]

More elaborate scheme.s can he envisaged. Thus, a. self-organizing neural network as obtained by the classification of a set of chemical reactions as outlined in Section 3,5 can be interfaced with the EROS system to select the reaction that acmaliy occurs from among various reaction alternatives. In this way, knowledge extracted from rcaetion databases can be interfaced with a reaction prediction system,... [Pg.552]

EINSTein (Enhanced ISAAC Neural Simulation Toolkit), was developed to address the basic question To what extent is land combat a self-organized complex... [Pg.593]

Polanski J, Jarzembek K, Gasteiger J. Self-organizing neural networks for screening and development of novel artificial sweetener candidates. Comb Chem High Throughput Screen 2000 3 481-95. [Pg.372]

T. Kohonen, Self Organization and Associated Memory. Springer-Verlag, Heidelberg, 1989. W.J. Meissen, J.R.M. Smits, L.M.C. Buydens and G. Kateman, Using artificial neural networks for solving chemical problems. II. Kohonen self-organizing feature maps and Hopfield networks. Chemom. Intell. Lab. Syst., 23 (1994) 267-291. [Pg.698]

Carpenter, G. A., and Grossberg, S., A massively parallel architecture for a self-organizing neural pattern recognition machine, Comput. Vis. Graphics Image Process 37,54 (1987b). [Pg.98]

All of the studies above have used back propagation multilayer perceptrons and many other varieties of neural network exist that have been applied to PyMS data. These include minimal neural networks,117119 radial basis functions,114120 self-organizing feature maps,110121 and autoassociative neural networks.122123... [Pg.332]

Includes an introduction to artificial intelligence, artificial neural networks, self-organizing maps, and growing cell structures... [Pg.341]


See other pages where Neural self-organizing is mentioned: [Pg.21]    [Pg.21]    [Pg.2852]    [Pg.193]    [Pg.497]    [Pg.618]    [Pg.621]    [Pg.1]    [Pg.8]    [Pg.443]    [Pg.555]    [Pg.740]    [Pg.743]    [Pg.754]    [Pg.764]    [Pg.775]    [Pg.797]    [Pg.835]    [Pg.688]    [Pg.2]    [Pg.267]    [Pg.357]    [Pg.153]    [Pg.430]    [Pg.21]    [Pg.98]    [Pg.202]    [Pg.285]   
See also in sourсe #XX -- [ Pg.193 , Pg.458 , Pg.545 ]




SEARCH



Kohonen self-organizing Neural Network

Neural networks Self-organizing map

Organic self-organizing

Self-organizing

Self-organizing neural network

© 2024 chempedia.info