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Artykuły w czasopismach na temat "Forecasting"
Суворов, Anatoliy Suvorov, Ивантер, Viktor Ivantyer, Сутягин i Valyeriy Sutyagin. "The Main Objectives and Principles of Socio-Economic Forecasting". Administration 3, nr 1 (17.03.2015): 8–17. http://dx.doi.org/10.12737/8785.
Pełny tekst źródłaZheng, Xiao Xia, i Fu Yang. "Research of Wind Speed and Wind Power Forecasting". Advanced Materials Research 347-353 (październik 2011): 611–14. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.611.
Pełny tekst źródłaRodrigues, Aaron. "Food Sales Forecasting Using Machine Learning Techniques: A Survey". International Journal for Research in Applied Science and Engineering Technology 9, nr 9 (30.09.2021): 869–72. http://dx.doi.org/10.22214/ijraset.2021.38069.
Pełny tekst źródłaReddy, Dr T. Koti. "Exchange Rate Forecasting". Indian Journal of Applied Research 1, nr 6 (1.10.2011): 120–24. http://dx.doi.org/10.15373/2249555x/mar2012/41.
Pełny tekst źródłaRathnayaka, R. M. Kapila Tharanga, D. M. K. N. Seneviratna i Wei Jianguo. "Grey system based novel approach for stock market forecasting". Grey Systems: Theory and Application 5, nr 2 (3.08.2015): 178–93. http://dx.doi.org/10.1108/gs-04-2015-0014.
Pełny tekst źródłaBAŞER, Uğur, Mehmet BOZOĞLU, Nevra ALHAS EROĞLU i Bakiye KILIÇ TOPUZ. "Forecasting Chestnut Production and Export of Turkey Using ARIMA Model". Turkish Journal of Forecasting 02, nr 2 (31.12.2018): 27–33. http://dx.doi.org/10.34110/forecasting.482789.
Pełny tekst źródłaArabi Belaghi, Reza, Minoo Aminnejad i Özlem Gürünlü Alma. "Stock Market Prediction Using Nonparametric Fuzzy and Parametric GARCH Methods". Turkish Journal of Forecasting 02, nr 1 (1.09.2018): 1–8. http://dx.doi.org/10.34110/forecasting.420126.
Pełny tekst źródłaZewdie, Mulugeta Aklilu, Gebretsadik G. Wubit i Amare W. Ayele. "G-STAR Model for Forecasting Space-Time Variation of Temperature in Northern Ethiopia". Turkish Journal of Forecasting 02, nr 1 (1.09.2018): 9–19. http://dx.doi.org/10.34110/forecasting.437599.
Pełny tekst źródłaKılıç Topuz, Bakiye, Mehmet Bozoğlu, Uğur Başer i Nevra Alhas Eroğlu. "Forecasting of Apricot Production of Turkey by Using Box-Jenkins Method". Turkish Journal of Forecasting 02, nr 2 (31.12.2018): 20–26. http://dx.doi.org/10.34110/forecasting.482914.
Pełny tekst źródłaMACİT, İrfan. "Estimating Risk Pressure Factor (RPF) with Artificial Neural Network (ANN) to Locate Search and Rescue (SAR) Team Station." Turkish Journal of Forecasting 03, nr 1 (31.08.2019): 26–38. http://dx.doi.org/10.34110/forecasting.484765.
Pełny tekst źródłaRozprawy doktorskie na temat "Forecasting"
Warren, Steven W. MATHEMATICAL MODELS WEATHER FORECASTING WEATHER PREDICTIONS MODELS REDUCTION PHYSICS OCEANOGRAPHY POWER REGRESSION ANALYSIS NAVY COMPARISON FORECASTING THESES. "Ensemble forecasting techniques in medium-range forecasting /". Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA267443.
Pełny tekst źródłaThesis advisor(s): Wendell A. Nuss. "March 1993." Page 66 is missing (which includes Fig. 21 a-b). Bibliography: p. 109. Also available online.
Warren, Steven W. "Ensemble forecasting techniques in medium-range forecasting". Thesis, Monterey, California. Naval Postgraduate School, 1993. http://hdl.handle.net/10945/39902.
Pełny tekst źródłaA continuing trend in numerical weather prediction (NWP) is the desire for reduced model forecast error. Developments in NWP such as advanced computing power and improved model physics and analysis methods have been successful in lowering error but are potentially limited The regression method of ensemble forecasting is used to further reduce mean forecast error when compared to individual model forecast performances. A statistical regression scheme is utilized to achieve an optimum combination fitting of the National Meteorological Center, the European Centre for Medium-Range Weather Forecasts, and the U.S. Navy Fleet Numerical Oceanography Center forecast models. The performance of the regression model is evaluated for 72-h and 108-h prediction cycles through statistical and subjective comparisons with the individual models and an equally weighted ensemble model at the surface and at 500 hPa. The regression model is shown to produce gains through the reduction of systematic error present in the individual model forecasts...
Abdullah, Rozi. "Rainfall forecasting algorithms for real time flood forecasting". Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296151.
Pełny tekst źródłaRasmussen, Steven R. "Forecasting 5" /". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA304364.
Pełny tekst źródłaJessen, Andreas, i Carina Kellner. "Forecasting Management". Thesis, University of Kalmar, Baltic Business School, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hik:diva-1868.
Pełny tekst źródłaIn a world that is moving faster and faster, a company’s ability to align to market changes is becoming a major competitive factor. Forecasting enables companies to predict what lies ahead, e.g. trend shifts or market turns, and makes it possible to plan for it. But looking into the future is never an easy task.
“Prediction is very difficult, especially if it’s about the future.” (Niels Bohr, 1885-1962)
However, progress in the field of forecasting has shown that it is possible for companies to improve on forecasting practices. This master thesis looks at the sales forecasting practices in MNCs primarily operating in emerging and developing countries. We examine the whole process of sales forecasting, also known as forecasting management, in order to develop a comprehensive model for forecasting in this type of companies. The research is based on a single case study, which is then later generalized into broader conclusions.
The conclusion of this master thesis is that forecasting is a four-step exercise. The four stages we have identified are: Knowledge creation, knowledge transformation, knowledge use and feedback. In the course of these four stages a company’s sales forecast is developed, changed and used. By understanding how each stage works and what to focus on, companies will be able to improve their forecasting practices.
Minkah, Richard. "Forecasting volatility". Thesis, Uppsala University, Department of Mathematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121079.
Pełny tekst źródłaMayr, Johannes. "Forecasting Macroeconomic Aggregates". Diss., lmu, 2010. http://nbn-resolving.de/urn:nbn:de:bvb:19-111404.
Pełny tekst źródłaNoble, Christopher J. "Forecasting vortex filaments". Thesis, University of Canterbury. Physics, 1998. http://hdl.handle.net/10092/8165.
Pełny tekst źródłaCHRISTO, ELIANE DA SILVA. "REACTIVE POWER FORECASTING". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=7622@1.
Pełny tekst źródłaNo novo modelo do Setor Elétrico é essencial desenvolver novas técnicas que estimem valores futuros, a curto e longo-prazos, das potências ativa e reativa. Com base nisso, este trabalho tem por objetivo apresentar uma nova técnica de previsão horária de potência reativa a curto-prazo, por subestação, baseada na linearidade existente entre as potências ativa e reativa. O modelo proposto, denominado de Modelo Híbrido de Previsão de Reativo, é dividido em duas etapas: A primeira etapa é feita uma classificação dos dados através de uma rede neural não supervisionada Mapas Auto-Organizáveis de Kohonen (SOM); A segunda etapa, utiliza-se um modelo de defasagem distribuída auto-regressivo (ADL) com estimação de Mínimos Quadrados Reponderados Iterativamente (IRLS) acoplado a uma correção para autocorrelação serial dos resíduos - Método Iterativo de Cochrane-Orcutt. Este Modelo Híbrido tem como variável dependente a potência reativa, e como variáveis explicativas dados horários de potência ativa e reativa no instante atual e defasadas no tempo. A previsão de potência reativa a curto-prazo é dividida em in sample e em out of sample. A previsão out of sample é aplicada a períodos horários em até um mês à frente. O modelo proposto é aplicado aos dados de uma concessionária específica de Energia Elétrica e os resultados são comparados a um modelo de Regressão Dinâmica convencional e a um modelo de Redes Neurais Artificiais Feedforward de Múltiplas camadas (MLP) com um algoritmo de retropropagação do erro.
The forecasting of reactive and active power is an important tool in the monitoring of an Electrical Energy System. The main purpose of the present work is the development of a new short-term reactive power hourly forecast technique, which can be used at utility or substations levels. The proposed model, named A Hybrid Model for Reactive Forecasting, is divided in two stages. In the first stage, the active and reactive power data are classified by an unsupervised neural network - the Self-Organized Maps of Kohonen (SOM). In the second stage, a Autoregressive Distributed Lags Model (ADL) is used with its parameters estimated by an Iteratively Reweighted Least Square (IRLS). It also includes a correction lag structure for serial autocorrelation of the residuals as used in the Cochrane-Orcutt formulation. The short term reactive power forecasting is divided in in sample and out of sample. The out of sample forecast is applied to hourly periods until one month ahead. The proposed model is applied to real data of one substation and the results are compared with two other approaches, a conventional Dynamic Regression and a Feedforward Multi-layer Perceptron (MLP) Artificial Neural Network model.
Binter, Roman. "Applied probabilistic forecasting". Thesis, London School of Economics and Political Science (University of London), 2012. http://etheses.lse.ac.uk/559/.
Pełny tekst źródłaKsiążki na temat "Forecasting"
McAuliffe, Bill. Forecasting. Mankato, MN: Creative Education, 2010.
Znajdź pełny tekst źródłaFildes, Robert, i P. Allen. Forecasting. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2011. http://dx.doi.org/10.4135/9781446261668.
Pełny tekst źródłaHirschmann, Kris. Forecasting! Edina, MN: ABDO Pub., 2008.
Znajdź pełny tekst źródłaAllen, P. Geoffrey, i Robert Fildes. Forecasting. Los Angeles, Calif: SAGE, 2011.
Znajdź pełny tekst źródłaNational Research Council (U.S.). Transportation Research Board. Transportation Data, Economics, and Forecasting Section. i National Research Council (U.S.). Transportation Research Board. Meeting, red. Forecasting. Washington, D.C: Transportation Research Board, National Research Council, 1989.
Znajdź pełny tekst źródłaD, Lawrence Kenneth, Geurts Michael i Guerard John B, red. Forecasting. Greenwich, Conn: JAI Press, 1998.
Znajdź pełny tekst źródłaLatham, Donna. Weather forecasting. Glenview, Ill: Pearson/Scott Foresman, 2010.
Znajdź pełny tekst źródłaCentre, Nottingham Fashion. Trend forecasting. Nottingham: Nottingham Fashion Centre, 1999.
Znajdź pełny tekst źródłaMolnar, Alan T. Economic forecasting. New York: Nova Science Publishers, 2010.
Znajdź pełny tekst źródłaCarnot, Nicolas, Vincent Koen i Bruno Tissot. Economic Forecasting. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815.
Pełny tekst źródłaCzęści książek na temat "Forecasting"
Khan, Arshad. "Forecasting". W Jumpstart Tableau, 331–36. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1934-8_36.
Pełny tekst źródłaBronzite, Michael. "Forecasting". W System Development, 83–99. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0469-8_6.
Pełny tekst źródłaChristou, Ioannis T. "Forecasting". W Quantitative Methods in Supply Chain Management, 139–202. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-766-2_2.
Pełny tekst źródłaLeininger, Arndt. "Forecasting". W Handbuch Methoden der Politikwissenschaft, 651–69. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-16936-7_36.
Pełny tekst źródłaLeininger, Arndt. "Forecasting". W Handbuch Organisationssoziologie, 1–20. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-16937-4_36-1.
Pełny tekst źródłaLeininger, Arndt. "Forecasting". W Handbuch Organisationssoziologie, 1–20. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-16937-4_36-2.
Pełny tekst źródłaThomopoulos, Nick T. "Forecasting". W Elements of Manufacturing, Distribution and Logistics, 1–27. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26862-0_1.
Pełny tekst źródłaRunkler, Thomas A. "Forecasting". W Data Analytics, 79–83. Wiesbaden: Vieweg+Teubner Verlag, 2012. http://dx.doi.org/10.1007/978-3-8348-2589-6_7.
Pełny tekst źródłaSwift, Louise. "Forecasting". W Mathematics and Statistics for Business, Management and Finance, 864–904. London: Macmillan Education UK, 1997. http://dx.doi.org/10.1007/978-1-349-25273-2_19.
Pełny tekst źródłaDe Gooijer, Jan G. "Forecasting". W Elements of Nonlinear Time Series Analysis and Forecasting, 391–437. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-43252-6_10.
Pełny tekst źródłaStreszczenia konferencji na temat "Forecasting"
Shetty, Sachin, Valentina Gori, Gianni Bagni i Giacomo Veneri. "Sensor Virtualization for Anomaly Detection of Turbo-Machinery Sensors—An Industrial Application". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039096.
Pełny tekst źródłaLanzilotta, Bibiana, Gabriela Mordecki, Pablo Tapie i Joaquín Torres. "Uncertainty and Business Cycle: An Empirical Analysis for Uruguay". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039097.
Pełny tekst źródłaTabib, Mandar, Kristoffer Skare, Endre Bruaset i Adil Rasheed. "Data-Driven Spatio-Temporal Modelling and Optimal Sensor Placement for a Digital Twin Set-Up". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039098.
Pełny tekst źródłaOladeji, Jonathan D., Benita G. Zulch i Joseph A. Yacim. "Predictive Accuracy of Logit Regression for Data-Scarce Developing Markets: A Nigeria and South Africa Study". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039100.
Pełny tekst źródłaMononen, Asko, Ari Alamäki, Janne Kauttonen, Aarne Klemetti, Anu Passi-Rauste i Harri Ketamo. "Forecasted Self: AI-Based Careerbot-Service Helping Students with Job Market Dynamics". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039099.
Pełny tekst źródłaValenzuela, Olga, Fernando Rojas, Luis Javier Herrera, Hector Pomares i Ignacio Rojas. "New Developments in Time Series and Forecasting, ITISE-2023". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039101.
Pełny tekst źródłaEdwards, Samuel J., Matthew D. Collette i Armin W. Troesch. "Extreme Characteristics of a Stochastic Non-Stationary Duffing Oscillator". W International Conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/engproc2023039102.
Pełny tekst źródłaAlander, Juha, Lauri Honkasilta i Kalle Saastamoinen. "Simulating the Aerial Ballet: The Dance of Fire-Fighting Planes and Helicopters". W International conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2024. http://dx.doi.org/10.3390/engproc2024068054.
Pełny tekst źródłaAhmad, Farooq, Livio Finos i Mariangela Guidolin. "Modeling the Future of Hydroelectric Power: A Cross-Country Study". W International conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2024. http://dx.doi.org/10.3390/engproc2024068056.
Pełny tekst źródłaMontante, Carmin, i Clemente Hernandez-Rodriguez. "Evaluation of Economic Interventions in Economic Blocks during an Economic and Sanitary Crisis". W International conference on Time Series and Forecasting. Basel Switzerland: MDPI, 2024. http://dx.doi.org/10.3390/engproc2024068055.
Pełny tekst źródłaRaporty organizacyjne na temat "Forecasting"
Cook, Steve. Directional Forecasting, Forecasting Accuracy and Making Profits. Bristol, UK: The Economics Network, wrzesień 2014. http://dx.doi.org/10.53593/n2703a.
Pełny tekst źródłaStock, James, i Mark Watson. Forecasting Inflation. Cambridge, MA: National Bureau of Economic Research, marzec 1999. http://dx.doi.org/10.3386/w7023.
Pełny tekst źródłaXiong, Yingge, Jon Fricker i Kevin McNamara. Socioeconomic Forecasting. Purdue University, grudzień 2012. http://dx.doi.org/10.5703/1288284314664.
Pełny tekst źródłaRosenzweig, Mark, i Christopher Udry. Forecasting Profitability. Cambridge, MA: National Bureau of Economic Research, sierpień 2013. http://dx.doi.org/10.3386/w19334.
Pełny tekst źródłaHyman, Ellis, Roger Shi, Mark Czarnaski i Sethu Raman. Atmospheric Forecasting. Fort Belvoir, VA: Defense Technical Information Center, październik 2000. http://dx.doi.org/10.21236/ada384012.
Pełny tekst źródłaAndersen, Torben, Tim Bollerslev, Peter Christoffersen i Francis Diebold. Volatility Forecasting. Cambridge, MA: National Bureau of Economic Research, marzec 2005. http://dx.doi.org/10.3386/w11188.
Pełny tekst źródłaSchwarz, Kurt F., IV Brooks i Thomas L. Forecasting Contracting Workload. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 1989. http://dx.doi.org/10.21236/ada211935.
Pełny tekst źródłaBaluga, Anthony, i Masato Nakane. Maldives Macroeconomic Forecasting:. Asian Development Bank, grudzień 2020. http://dx.doi.org/10.22617/wps200431-2.
Pełny tekst źródłaRoberts, Benedict C. Multiple Forecasting Techniques. Fort Belvoir, VA: Defense Technical Information Center, grudzień 1990. http://dx.doi.org/10.21236/ada230600.
Pełny tekst źródłaGaregnani, Lorena, i Maximiliano Gómez Aguirre. Forecasting Inflation in Argentina. Inter-American Development Bank, czerwiec 2018. http://dx.doi.org/10.18235/0001160.
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