FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2794025662> ?p ?o ?g. }

• W2794025662 endingPage "1" @default.
• W2794025662 startingPage "1" @default.
• W2794025662 abstract "first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessEditorial Forecasting: A New Open Access Journal Dealing with Time Series Analysis and Forecasting by Ignacio Rojas Department of Computer Architecture and Computer Technology, CITIC-UGR, University of Granada, 18071 Granada, Spain Forecasting 2019, 1(1), 1-2; https://doi.org/10.3390/forecast1010001 Received: 5 March 2018 / Revised: 6 March 2018 / Accepted: 6 March 2018 / Published: 9 March 2018 Download Download PDF Download PDF with Cover Download XML Download Epub Versions Notes Welcome to Forecasting, a new, online, open access journal, which provides an advanced forum for studies related to forecasting: theoretical, practical, computational and methodological. It publishes regular research papers, communications, letters, short notes and reviews.The main editorial objective for Forecasting is to provide a forum for advanced research, with topics of interest including, but not limited to, methodology of forecasting, forecasting complex/big data, time series analysis and forecasting, evaluation and implementation of forecasting methods and approaches, hybrid advanced methodologies with evolutionary computation techniques to improve forecasting accuracy, limitations of forecasting, etc. Also relevant is the application of forecasting in different areas, including (but not limited to) atmospheric science forecasting, climate forecasting, economic and econometric forecasting, demand planning, supply chain management, energy forecasting, hydrological forecasting, health forecasting, industrial production values forecasting, marketing forecasting, software reliability forecasting, traffic forecasting, and tourism forecasting.From the measurements of natural phenomena such as the number of rays in a storm, the amount of rainfall or temperature in a given region, to the electricity consumption of a city or a country, they can all be considered as a mere succession of values obtained, normally at regular intervals, or a time series. The usefulness of the study of time series and forecasting is of huge importance for our society in general. At this point, it should be noted that there are many types of time series caused by different phenomena, and there therefore exist many different behaviors. If the phenomena behind a series were known with enough accuracy, we would be able to build a model from them, making prediction easy, direct and accurate. However, most phenomena are not known or, at least, are not known with sufficient precision; thus, obtaining a model from the phenomena becomes unfeasible, unless we are able to infer the model from the values of the series in order to forecast future values.The applications in this field are enormous, and include energy forecasting or economic analysis of stock indices prediction, climate forecasting, chemical or natural process forecasting, etc. It can be affirmed that forecasting is a transversal field of research encompassing multiple disciplines.Our aim is to encourage researchers to publish their experimental, theoretical and computational results in as much detail as necessary. Articles and review papers are also welcomed. There is no restriction on paper length or number of figures and tables, allowing authors to explain their scientific content thoroughly.We would like to take this opportunity to thank all the authors, reviewers and Editorial Board members of Forecasting for their future contributions and help. Together, we can create and encourage the new journal Forecasting to become a premier interdisciplinary journal on forecasting and time series analysis. Our task is to realize a fast publication process for high-quality contributions on relevant topics within forecasting. We would also like to thank the MDPI Editorial Office for their support.In conclusion, on behalf of the Editorial Board, let me cordially invite the international scientific community in the field of forecasting and time series analysis to choose this new exciting journal; we look forward to receiving your research contributions. Thank you all in advance. Conflicts of InterestThe author declares no conflict of interest. © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style Rojas, I. Forecasting: A New Open Access Journal Dealing with Time Series Analysis and Forecasting. Forecasting 2019, 1, 1-2. https://doi.org/10.3390/forecast1010001 AMA Style Rojas I. Forecasting: A New Open Access Journal Dealing with Time Series Analysis and Forecasting. Forecasting. 2019; 1(1):1-2. https://doi.org/10.3390/forecast1010001 Chicago/Turabian Style Rojas, Ignacio. 2019. Forecasting: A New Open Access Journal Dealing with Time Series Analysis and Forecasting Forecasting 1, no. 1: 1-2. https://doi.org/10.3390/forecast1010001 Find Other Styles Article Metrics No No Article Access Statistics For more information on the journal statistics, click here. Multiple requests from the same IP address are counted as one view." @default.
• W2794025662 created "2018-03-29" @default.
• W2794025662 creator A5089029287 @default.
• W2794025662 date "2018-03-09" @default.
• W2794025662 modified "2023-10-14" @default.
• W2794025662 title "Forecasting: A New Open Access Journal Dealing with Time Series Analysis and Forecasting" @default.
• W2794025662 doi "https://doi.org/10.3390/forecast1010001" @default.
• W2794025662 hasPublicationYear "2018" @default.
• W2794025662 type Work @default.
• W2794025662 sameAs 2794025662 @default.
• W2794025662 citedByCount "2" @default.
• W2794025662 countsByYear W27940256622021 @default.
• W2794025662 countsByYear W27940256622023 @default.
• W2794025662 crossrefType "journal-article" @default.
• W2794025662 hasAuthorship W2794025662A5089029287 @default.
• W2794025662 hasBestOaLocation W27940256621 @default.
• W2794025662 hasConcept C122282355 @default.
• W2794025662 hasConcept C127413603 @default.
• W2794025662 hasConcept C136764020 @default.
• W2794025662 hasConcept C153294291 @default.
• W2794025662 hasConcept C154945302 @default.
• W2794025662 hasConcept C193809577 @default.
• W2794025662 hasConcept C205649164 @default.
• W2794025662 hasConcept C21001229 @default.
• W2794025662 hasConcept C2780154274 @default.
• W2794025662 hasConcept C41008148 @default.
• W2794025662 hasConcept C42475967 @default.
• W2794025662 hasConcept C49937458 @default.
• W2794025662 hasConceptScore W2794025662C122282355 @default.
• W2794025662 hasConceptScore W2794025662C127413603 @default.
• W2794025662 hasConceptScore W2794025662C136764020 @default.
• W2794025662 hasConceptScore W2794025662C153294291 @default.
• W2794025662 hasConceptScore W2794025662C154945302 @default.
• W2794025662 hasConceptScore W2794025662C193809577 @default.
• W2794025662 hasConceptScore W2794025662C205649164 @default.
• W2794025662 hasConceptScore W2794025662C21001229 @default.
• W2794025662 hasConceptScore W2794025662C2780154274 @default.
• W2794025662 hasConceptScore W2794025662C41008148 @default.
• W2794025662 hasConceptScore W2794025662C42475967 @default.
• W2794025662 hasConceptScore W2794025662C49937458 @default.
• W2794025662 hasIssue "1" @default.
• W2794025662 hasLocation W27940256621 @default.
• W2794025662 hasLocation W27940256622 @default.
• W2794025662 hasOpenAccess W2794025662 @default.
• W2794025662 hasPrimaryLocation W27940256621 @default.
• W2794025662 hasRelatedWork W1994174876 @default.
• W2794025662 hasRelatedWork W2006711199 @default.
• W2794025662 hasRelatedWork W2286104964 @default.
• W2794025662 hasRelatedWork W2794025662 @default.
• W2794025662 hasRelatedWork W2899548489 @default.
• W2794025662 hasRelatedWork W3081484245 @default.
• W2794025662 hasRelatedWork W3166393081 @default.
• W2794025662 hasRelatedWork W4310372331 @default.
• W2794025662 hasRelatedWork W4362706849 @default.
• W2794025662 hasRelatedWork W475112967 @default.
• W2794025662 hasVolume "1" @default.
• W2794025662 isParatext "false" @default.
• W2794025662 isRetracted "false" @default.
• W2794025662 magId "2794025662" @default.
• W2794025662 workType "article" @default.