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Associative neural network

The 2D model was built from a wide array of descriptors, including also E-state indices, by Simulations Plus [89], The model is based on the associative neural network ensembles [86, 87] constructed from n=9658 compounds selected from the BioByte StarList [10] of ion-corrected experimental logP values. The model produced MAE = 0.24, r = 0.96 (R. Fraczkiewicz, personal communication). [Pg.394]

Tetko, I. V., Tandiuk, V. Y. Application of associative neural networks for prediction of lipophilicity in ALOGPS 2.1 program. [Pg.405]

Tetko, I. V. Neural network studies. 4. Introduction to associative neural networks. J. Chem. Inf. Comput. Sci. 2002, 42, 717-728. [Pg.437]

Associative neural networks (ASNN) Aqueous solubility, octanol-water partition (logP, logD) Quantitative Error No [13-15]... [Pg.31]

Tetko, I.V. Associative neural network. Neural Process. Lett. 2002, 16 (2), 187-199. [Pg.355]

Methods Using 2D and ID Descriptors A good number of articles on aqueous solubility used a nonlinear method of data analysis, in particular, for methods developed with ID and 2D descriptors. Huuskonen [16] used E-state indexes [52,53] and several other topological indexes, with a total of 30 indexes, to develop his models. The predicted results for the 413 test set, SE = 0.71, calculated with MLRA were improved with a neural network, resulting in SE = 0.6. Tetko [17] noticed that E-state indexes represent a complete system of descriptors for molecules, and thus only these descriptors are sufficient to develop the aqueous solubility model. Indeed the model developed by the authors using exclusively E-state indexes provides similar results when compared to the model of Huuskonen [16]. Later on, the model was redeveloped using the Associative Neural Network (ASNN) method [54],... [Pg.249]

Tetko IV. Neural network studies 4. Introduction to associative neural networks. [Pg.270]

SANZ, X PERERA, R, HUERTA, C. (2007) Fault diagnosis of rotating machinery based on auto-associative neural networks and wavelet transforms. Joiunal of Sound and Vibration, 302 (4-5), pp. 981-999. [Pg.202]

Atul Sethi, Siddharth Arora, Abhishek Ballaney, Frequency domain analysis of ECG signals using auto-associative neural networks, International Conference on Biomedical and Pharmaceutical Engineering 2006 (ICBPE 2006), 531-536... [Pg.402]


See other pages where Associative neural network is mentioned: [Pg.274]    [Pg.394]    [Pg.397]    [Pg.436]    [Pg.389]    [Pg.75]    [Pg.325]    [Pg.337]    [Pg.26]    [Pg.28]    [Pg.249]    [Pg.254]    [Pg.59]    [Pg.512]    [Pg.194]    [Pg.1789]    [Pg.90]    [Pg.112]    [Pg.37]    [Pg.82]    [Pg.66]   
See also in sourсe #XX -- [ Pg.397 , Pg.405 , Pg.406 ]




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