Abstract
This work is a logical extension of the works of Shurygin over the period from 1994 to 1996 and is devoted to the development of approaches to the stable estimation of the parameters of regression models. The results obtained earlier are extended to the cases of a nonlinear regression and a feedforward neural network with one hidden layer. Theoretical results are confirmed by numerical experiments. The problem of numerical modeling consisted in the construction of a system for the prediction of a change in the Gibbs free energy (Δ G) in the course of the formation of protein-protein and protein-ligand complexes. For the training set, data on 150 complexes of a various nature are used, for which there exists an experimental estimate (Δ G). For independent variables, different rated values of the physicochemical parameters of data for complexes are used.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
REFERENCES
Huber, P.J., Robust Statistics, New York: Wiley, 1981.
Shurygin, A.M., Regression: Choice of a Model and Stable Estimation, Avtom.Telemekh., 1996, no. 6, pp. 104–115.
Shurygin, A.M., Prikladnaya stokhastika: robastnost', otsenivanie, prognoz (Applied Stochastics: Robustness, Estimation, Prediction), Moscow: Finansy i Statistika, 2000.
Meshalkin, L.D., Ispol'zovanie vesovoi funktsii pri otsenke regressionnoi zavisimosti.Mnogomernyi statisticheskii analiz v sotsial'no-ekonomicheskikh issledovaniyakh (Use of the Weight Function in Estimation of the Regression Relation. Multidimensional Statistical Analysis in Social-Economic Investigations), Moscow: Nauka, 1974.
Aivazyan, S.A., Bukhshtaber, V.M., Enyukov, I.S. and Meshalkin, L.D., Prikladnaya statistika: klassi fikatsiya i snizhenie razmernosti (Applied Statistics: Classification and Reduction of the Dimension), Moscow: Finansy i Statistika, 1989.
Aivazyan, S.A., Enyukov, I.S., and Meshalkin, L.D., Prikladnaya statistika: issledovanie zavisimostei (Applied Statistics: Investigation of Relations), Moscow: Financy i Statistika, 1985.
Gorban', A.N., Algoritmy i programmy bystrogo obucheniya neironnykh setei (Algorithms and Programs of Fast Training of Neural Networks), Novosibirsk: Nauka, 1992.
Gorban', A.N. and Rossiev, D.A., Neironnye seti na personal'mon komp'yutere (Neural Networks on a Personal Computer), Novosibirsk: Nauka, 1996.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Belkina, N.V., Krepets, V.V. & Shakin, V.V. On Stable Estimation of the Parameters of Feedforward Neural Networks in Dealing with Biological Objects. Automation and Remote Control 63, 66–75 (2002). https://doi.org/10.1023/A:1013783319376
Issue Date:
DOI: https://doi.org/10.1023/A:1013783319376