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dc.contributor.advisorHuamán Tuesta, José Roberto
dc.contributor.authorSaldaña Olivas, Edu Guillermo
dc.date.accessioned2021-09-01T14:56:08Z
dc.date.available2021-09-01T14:56:08Z
dc.date.issued2021-03-27
dc.identifier.citationSaldaña, E. G. (2021). Extreme learning machine for business sales forecasts: a systematic review (Tesis de licenciatura). Repositorio de la Universidad Privada del Norte. Recuperado de https://hdl.handle.net/11537/27695es_PE
dc.identifier.other.es_PE
dc.identifier.urihttps://hdl.handle.net/11537/27695
dc.description.abstractABSTRACT Technology in business is vital, in recent decades technology has optimized the way they are managed making operations faster and more efficient, so we can say that companies need technology to stay in the market. This systematic review aims to determine to what extent an Extreme Learning Machine (ELM) system helps sales forecasts (SF) of companies, based on the scientific literature of the last 17 years. For the methodology, the systematic search for keywords began in the repositories of Google Scholar, Scielo, Redalyc, among others. Documents were collected between 2002 and 2019 and organized according to an eligibility protocol defined by the author. As an inclusion criteria, the sources in which their conclusions contributed to deepening the investigation were taken and those that did not contribute were excluded. Each of the results represented in graphs was discussed. The main limitation was the little information on the subject because it is a new topic. In conclusion, an ELM system makes use of both internal and external data to develop a more precise SF, which can be used not only by the sales and finance area but also to coordinate with the production area a more exact batch to be produced; this has a great impact on the communication and dynamism of companies to reduce costs and increase profits. KEYWORDS: business sales forecast, extreme learning machine, systematic reviewes_PE
dc.description.uriTesises
dc.formatapplication/pdfes_PE
dc.formatapplication/mswordes_PE
dc.language.isospaes_PE
dc.publisherUniversidad Privada del Nortees_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.sourceUniversidad Privada del Nortees_PE
dc.sourceRepositorio Institucional - UPNes_PE
dc.subjectVentases_PE
dc.subjectPredicción de las ventases_PE
dc.subjectInnovaciones tecnológicases_PE
dc.titleExtreme learning machine for business sales forecasts: a systematic reviewes_PE
dc.typeinfo:eu-repo/semantics/bachelorThesises_PE
thesis.degree.grantorUniversidad Privada del Norte. Facultad de Negocioses_PE
thesis.degree.levelLicenciaturaes
thesis.degree.disciplineAdministración y Negocios Internacionaleses_PE
thesis.degree.nameLicenciado en Administración y Negocios Internacionaleses_PE
dc.publisher.countryPEes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#5.02.01es_PE
thesis.degree.programPregradospa
dc.description.sedeTrujillo El Molinoes_PE
renati.advisor.dni17814526
renati.advisor.orcidhttps://orcid.org/0000-0001-7700-9116es_PE
renati.author.dni70857486
renati.discipline413316
renati.jurorMaguiña Rivero, Omar Fabricio
renati.jurorGarcía Gutti, Alan Enrique
renati.jurorParedes León, Francisco Jesús
renati.levelhttps://purl.org/pe-repo/renati/level#tituloProfesionales_PE
renati.typehttps://purl.org/pe-repo/renati/type#tesises_PE


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