eprintid: 19093
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/90/93
datestamp: 2024-06-04 14:11:32
lastmod: 2024-06-04 14:11:32
status_changed: 2024-06-04 14:04:51
type: book
metadata_visibility: show
creators_name: Bavoh, C.B.
creators_name: Lal, B.
title: Machine Learning Application Guidelines in Flow Assurance
ispublished: pub
note: cited By 0
abstract: In this chapter guidelines for conducting an effective machine learning based prediction models in flow assurance areas is presented with much emphasis of data availability, data representation and model selection. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
date: 2023
publisher: Springer Nature
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174776536&doi=10.1007%2f978-3-031-24231-1_10&partnerID=40&md5=929af7ae1450461801a9457b6fb11f27
id_number: 10.1007/978-3-031-24231-1₁₀
full_text_status: none
publication: Machine Learning and Flow Assurance in Oil and Gas Production
pagerange: 175-177
refereed: TRUE
isbn: 9783031242311; 9783031242304
citation:   Bavoh, C.B. and Lal, B.  (2023) Machine Learning Application Guidelines in Flow Assurance.     Springer Nature, pp. 175-177.  ISBN 9783031242311; 9783031242304