{"id":"https://openalex.org/W2243352493","doi":"https://doi.org/10.2312/eurova.20151107","title":"Integrating Predictions in Time Series Model Selection","display_name":"Integrating Predictions in Time Series Model Selection","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2243352493","doi":"https://doi.org/10.2312/eurova.20151107","mag":"2243352493"},"language":"en","primary_location":{"id":"doi:10.2312/eurova.20151107","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eurova.20151107","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/eurova.20151107","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032676799","display_name":"Markus B\u00f6gl","orcid":"https://orcid.org/0000-0002-8337-4774"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"B\u00f6gl, Markus","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005355207","display_name":"Wolfgang Aigner","orcid":"https://orcid.org/0000-0001-5762-1869"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aigner, Wolfgang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041191852","display_name":"Peter Filzmoser","orcid":"https://orcid.org/0000-0002-8014-4682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Filzmoser, Peter","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079997473","display_name":"Theresia Gschwandtner","orcid":"https://orcid.org/0000-0002-9555-3374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gschwandtner, Theresia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075562509","display_name":"Tim Lammarsch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lammarsch, Tim","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019622072","display_name":"Silvia Miksch","orcid":"https://orcid.org/0000-0003-4427-5703"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miksch, Silvia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027673731","display_name":"Alexander Rind","orcid":"https://orcid.org/0000-0001-8788-4600"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rind, Alexander","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5032676799"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.9682999849319458,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6975809335708618},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6542508602142334},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.6295826435089111},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6016445159912109},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5824432373046875},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5668022036552429},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5438464879989624},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5101111531257629},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5011029243469238},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4352780878543854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39922913908958435},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15040045976638794}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6975809335708618},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6542508602142334},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6295826435089111},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6016445159912109},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5824432373046875},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5668022036552429},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5438464879989624},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5101111531257629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5011029243469238},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4352780878543854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39922913908958435},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15040045976638794},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/eurova.20151107","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eurova.20151107","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.2312/eurova.20151107","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eurova.20151107","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1486034269","https://openalex.org/W1977294046","https://openalex.org/W1980462675","https://openalex.org/W1987793895","https://openalex.org/W2007926133","https://openalex.org/W2089741653","https://openalex.org/W2097924927","https://openalex.org/W2126483201","https://openalex.org/W2126831543","https://openalex.org/W2136827748","https://openalex.org/W2138851433","https://openalex.org/W2477192109","https://openalex.org/W3150435615"],"related_works":["https://openalex.org/W2556122759","https://openalex.org/W2739776117","https://openalex.org/W2752569217","https://openalex.org/W3136280708","https://openalex.org/W3204198145","https://openalex.org/W1993537016","https://openalex.org/W3144828875","https://openalex.org/W2565502924","https://openalex.org/W1677875891","https://openalex.org/W2280847838","https://openalex.org/W3120178073","https://openalex.org/W1970956865","https://openalex.org/W1972013619","https://openalex.org/W86391880","https://openalex.org/W1502341498","https://openalex.org/W629964596","https://openalex.org/W3208808915","https://openalex.org/W2766907367","https://openalex.org/W2047860443","https://openalex.org/W2155575073"],"abstract_inverted_index":{"Time":[0],"series":[1,12,27,94,146],"appear":[2],"in":[3,10,57,70,100,116,123,161],"many":[4],"different":[5],"domains.":[6],"The":[7,23],"main":[8],"goal":[9],"time":[11,21,26,93,145],"analysis":[13],"is":[14,29,50,76,96,139],"to":[15,52,79,105,111,141,163],"find":[16],"a":[17,135],"model":[18,59,65,90,118],"for":[19,126],"given":[20],"series.":[22],"selection":[24,60,119],"of":[25,152,158],"models":[28,160],"done":[30],"iteratively":[31],"based,":[32],"usually,":[33],"on":[34],"information":[35],"criteria":[36],"and":[37,66,108,121,129,143,154],"residual":[38],"plots.":[39],"These":[40],"sources":[41],"may":[42],"show":[43],"only":[44],"small":[45],"variations":[46],"and,":[47],"therefore,":[48],"it":[49,75],"necessary":[51],"consider":[53],"the":[54,58,64,68,92,113,117,124,149,156,164],"prediction":[55,69,114,150,157],"capabilities":[56,115,151],"process.":[61],"When":[62],"applying":[63],"including":[67],"an":[71,127],"interactive":[72,137],"visual":[73,107,136],"interface":[74,138],"still":[77],"difficult":[78],"compare":[80,155],"deviations":[81],"from":[82],"actual":[83,165],"values":[84],"or":[85],"benchmark":[86],"models.":[87],"Judging":[88],"which":[89],"fits":[91],"adequately":[95],"not":[97],"well":[98],"supported":[99],"current":[101],"methods.":[102],"We":[103],"propose":[104],"combine":[106],"analytical":[109],"methods":[110],"integrate":[112],"process":[120],"assist":[122],"decision":[125],"adequate":[128],"parsimonious":[130],"model.":[131],"In":[132],"our":[133],"approach":[134],"used":[140],"select":[142],"adjust":[144],"models,":[147,153],"utilize":[148],"multiple":[159],"relation":[162],"values.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
