SUPPORT VECTOR REGRESSION WITH BAYESIAN PARAMETERS OPTIMIZATION FOR INCLINOMETER WELLS MEASUREMENTS REFINEMENT

Authors

  • A. Ryabov Arzamas Polytechnic Institute (branch) of N. Novgorod State Technic University

Keywords:

wells inclinometry; support vector machine; data regression; Bayesian optimization.

Abstract

This paper propose a method of inclinometer wells measurements refinement via support vector regression with Bayesian parameters optimization. The results demonstrate that the given method-based algorithm is efficient for wells inclinometer measurements correction.

Author Biography

A. Ryabov , Arzamas Polytechnic Institute (branch) of N. Novgorod State Technic University

Candidat of Science, assistant professor

References

Cortes, C., Vapnik, V., 1995. Support-vector networks. Machine learning 20, 273–297.

Smola, A.J., Schölkopf, B., 2004. A tutorial on support vector regression. Statistics and computing 14, 199–222.

Yeh, C.Y., Huang, C.W., Lee, S.J., 2011. A multiple-kernel support vector regression approach for stock market price forecasting. Expert Systems with Applications 38, 2177–2186.

M.A. Borisov, A.A. Gus'kov, S.I. Koshelev, 2016. Povyshenie tochnosti opredelenija traektorii skvazhiny giroinklinometrom za schet vtorichnoj obrabotki dannyh. Privolzhskij nauchnyj vestnik № 12-2 (64) – 2016, 11-14.

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Published

2021-12-30

Issue

Vol. 1 No. 74 (2021)

Section

Статьи

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