Applicability of LAMDA as classification model in the oil production
| Autor: | Jose Aguilar, Luis Morales, Edgar Camargo, Hector R. Lozada |
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| Rok vydání: | 2019 |
| Předmět: |
Linguistics and Language
business.industry Computer science Multivariable calculus ComputerApplications_COMPUTERSINOTHERSYSTEMS Context (language use) 02 engineering and technology Machine learning computer.software_genre Language and Linguistics Petroleum industry Artificial Intelligence 020204 information systems Oil production 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | Artificial Intelligence Review. 53:2207-2236 |
| ISSN: | 1573-7462 0269-2821 |
| DOI: | 10.1007/s10462-019-09731-6 |
| Popis: | This work analyzes the utilization of classification models in the context of the oil industry and presents examples of application. Particularly, we analyze three case studies, two to explain the behavior of oil wells that produce via artificial methods (the classification as a descriptive model), and another to predict the oil prices (the classification as a predictive model). The classification technique used in this work is LAMDA-HAD, which is an improvement to the well-known technique called learning algorithm multivariable and data analysis (LAMDA), that has been used in diagnostic tasks. Finally, the results with the descriptive and predictive models are discussed, in order to analyze the importance of the classification in the context of the oil business. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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