Machine Learning Algorithm For Efficiency Management Of Oil Well

DOI

10.2991/icence-16.2016.136How to use a DOI?

Keywords

Machine learning; pattern recognition; computer classification; application of oil field

Abstract

on machine learning technique and oil well efficiency project practical problem, to the complicated circumstance of oil well efficiency, non-linear machine learning support vector machines ( SVM ) shows a better analysis results than the classified prediction result of linear machine learning logistics regression ( LR ). This paper analyzed and derived the theorems and classification reason of logistics regression and support vector machines. The experiments calculated and compared the accuracies of these two algorithms under the same conditions, the result conforms the conclusion.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shi-qi Bao
AU  - Zhi-jie Ding
AU  - Yun-yun Wu
AU  - Yue-ting Shi
PY  - 2016/09
DA  - 2016/09
TI  - Machine Learning Algorithm For Efficiency Management Of Oil Well
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 726
EP  - 732
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.136
DO  - 10.2991/icence-16.2016.136
ID  - Bao2016/09
ER  -