Automatic model selection through machine learning

Automatic model selection through machine learning

A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Keli Sun, Xiao Bo Hong, Xiaoyan Zhong, Koji Ito
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DETECTING MASSES OR OBJECTS
GEOPHYSICS
GRAVITATIONAL MEASUREMENTS
MEASURING
PHYSICS
TESTING
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Keli Sun
Xiao Bo Hong
Xiaoyan Zhong
Koji Ito
description A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_GB2606957B</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>GB2606957B</sourcerecordid><originalsourceid>FETCH-epo_espacenet_GB2606957B3</originalsourceid><addsrcrecordid>eNrjZDByLC3Jz00syUxWyM1PSc1RKE7NSU0uyczPUyjJKMovTc9QyE1MzsjMS1XISU0sysvMS-dhYE1LzClO5YXS3Azybq4hzh66qQX58anFBYnJqXmpJfHuTkZmBmaWpuZOxoRVAABDQyuR</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Automatic model selection through machine learning</title><source>esp@cenet</source><creator>Keli Sun ; Xiao Bo Hong ; Xiaoyan Zhong ; Koji Ito</creator><creatorcontrib>Keli Sun ; Xiao Bo Hong ; Xiaoyan Zhong ; Koji Ito</creatorcontrib><description>A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DETECTING MASSES OR OBJECTS ; GEOPHYSICS ; GRAVITATIONAL MEASUREMENTS ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240228&amp;DB=EPODOC&amp;CC=GB&amp;NR=2606957B$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240228&amp;DB=EPODOC&amp;CC=GB&amp;NR=2606957B$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Keli Sun</creatorcontrib><creatorcontrib>Xiao Bo Hong</creatorcontrib><creatorcontrib>Xiaoyan Zhong</creatorcontrib><creatorcontrib>Koji Ito</creatorcontrib><title>Automatic model selection through machine learning</title><description>A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DETECTING MASSES OR OBJECTS</subject><subject>GEOPHYSICS</subject><subject>GRAVITATIONAL MEASUREMENTS</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDByLC3Jz00syUxWyM1PSc1RKE7NSU0uyczPUyjJKMovTc9QyE1MzsjMS1XISU0sysvMS-dhYE1LzClO5YXS3Azybq4hzh66qQX58anFBYnJqXmpJfHuTkZmBmaWpuZOxoRVAABDQyuR</recordid><startdate>20240228</startdate><enddate>20240228</enddate><creator>Keli Sun</creator><creator>Xiao Bo Hong</creator><creator>Xiaoyan Zhong</creator><creator>Koji Ito</creator><scope>EVB</scope></search><sort><creationdate>20240228</creationdate><title>Automatic model selection through machine learning</title><author>Keli Sun ; Xiao Bo Hong ; Xiaoyan Zhong ; Koji Ito</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_GB2606957B3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DETECTING MASSES OR OBJECTS</topic><topic>GEOPHYSICS</topic><topic>GRAVITATIONAL MEASUREMENTS</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>Keli Sun</creatorcontrib><creatorcontrib>Xiao Bo Hong</creatorcontrib><creatorcontrib>Xiaoyan Zhong</creatorcontrib><creatorcontrib>Koji Ito</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Keli Sun</au><au>Xiao Bo Hong</au><au>Xiaoyan Zhong</au><au>Koji Ito</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Automatic model selection through machine learning</title><date>2024-02-28</date><risdate>2024</risdate><abstract>A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_GB2606957B
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DETECTING MASSES OR OBJECTS
GEOPHYSICS
GRAVITATIONAL MEASUREMENTS
MEASURING
PHYSICS
TESTING
title Automatic model selection through machine learning
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T12%3A25%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Keli%20Sun&rft.date=2024-02-28&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EGB2606957B%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true