Готові списки джерел за темами / Forecasting function

Добірка наукової літератури з теми "Forecasting function"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Зміст

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Forecasting function".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Статті в журналах з теми "Forecasting function"

1

Sanders, Nada R. "Managing the forecasting function." Industrial Management & Data Systems 95, no. 4 (May 1995): 12–18. http://dx.doi.org/10.1108/02635579510086689.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Szewczak, Lara. "Finding Genetic Regulators, Forecasting Function." Cell 174, no. 2 (July 2018): 247–49. http://dx.doi.org/10.1016/j.cell.2018.06.043.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

A . OTHMAN, SAMEERAH, and SHELAN S . ISMAEL. "Forecasting rainfull using transfer function." IRAQI JOURNAL OF STATISTICAL SCIENCES 13, no. 24 (August 28, 2013): 17–44. http://dx.doi.org/10.33899/iqjoss.2013.80692.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Sen, Rituparna, and Changie Ma. "Forecasting Density Function: Application in Finance." Journal of Mathematical Finance 05, no. 05 (2015): 433–47. http://dx.doi.org/10.4236/jmf.2015.55037.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Mantica, Giorgio, and B. G. Giraud. "Nonlinear forecasting and iterated function systems." Chaos: An Interdisciplinary Journal of Nonlinear Science 2, no. 2 (April 1992): 225–30. http://dx.doi.org/10.1063/1.165908.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Sun, Sizhou, Jingqi Fu, Feng Zhu, and Nan Xiong. "A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization." Mathematical Problems in Engineering 2018 (November 14, 2018): 1–21. http://dx.doi.org/10.1155/2018/9287097.

Повний текст джерела
Анотація:
The aims of this study contribute to a new hybrid model by combining ensemble empirical mode decomposition (EEMD) with multikernel function least square support vector machine (MKLSSVM) optimized by hybrid gravitation search algorithm (HGSA) for short-term wind speed prediction. In the forecasting process, EEMD is adopted to make the original wind speed data decomposed into intrinsic mode functions (IMFs) and one residual firstly. Then, partial autocorrelation function (PACF) is applied to identify the correlation between the corresponding decomposed components. Subsequently, the MKLSSVM using multikernel function of radial basis function (RBF) and polynomial (Poly) kernel function by weight coefficient is exploited as core forecasting engine to make the short-term wind speed prediction. To improve the regression performance, the binary-value GSA (BGSA) in HGSA is utilized as feature selection approach to remove the ineffective candidates and reconstruct the most relevant feature input-matrix for the forecasting engine, while real-value GSA (RGSA) makes the parameter combination optimization of MKLSSVM model. In the end, these respective decomposed subseries forecasting results are combined into the final forecasting values by aggregate calculation. Numerical results and comparable analysis illustrate the excellent performance of the EEMD-HGSA-MKLSSVM model when applied in the short-term wind speed forecasting.
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Verma, Shilpa, G. T. Thampi, and Madhuri Rao. "ANN based method for improving gold price forecasting accuracy through modified gradient descent methods." IAES International Journal of Artificial Intelligence (IJ-AI) 9, no. 1 (March 1, 2020): 46. http://dx.doi.org/10.11591/ijai.v9.i1.pp46-57.

Повний текст джерела
Анотація:
Forecast of prices of financial assets including gold is of considerable importance for planning the economy. For centuries, people have been holding gold for many important reasons such as smoothening inflation fluctuations, protection from an economic crisis, sound investment etc.. Forecasting of gold prices is therefore an ever important exercise undertaken both by individuals and groups. Various local, global, political, psychological and economic factors make such a forecast a complex problem. Data analysts have been increasingly applying Artificial Intelligence (AI) techniques to make such forecasts. In the present work an inter comparison of gold price forecasting in Indian market is first done by employing a few classical Artificial Neural Network (ANN) techniques, namely Gradient Descent Method (GDM), Resilient Backpropagation method (RP), Scaled Conjugate Gradient method (SCG), Levenberg-Marquardt method (LM), Bayesian Regularization method (BR), One Step Secant method (OSS) and BFGS Quasi Newton method (BFG). Improvement in forecasting accuracy is achieved by proposing and developing a few modified GDM algorithms that incorporate different optimization functions by replacing the standard quadratic error function of classical GDM. Various optimization functions investigated in the present work are Mean median error function (MMD), Cauchy error function (CCY), Minkowski error function (MKW), Log cosh error function (LCH) and Negative logarithmic likelihood function (NLG). Modified algorithms incorporating these optimization functions are referred to here by GDM_MMD, GDM_CCY, GDM_KWK, GDM_LCH and GDM_NLG respectively. Gold price forecasting is then done by employing these algorithms and the results are analysed. The results of our study suggest that the forecasting efficiency improves considerably on applying the modified methods proposed by us.
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Levy, William B., Ashlie B. Hocking, and Xiangbao Wu. "Interpreting hippocampal function as recoding and forecasting." Neural Networks 18, no. 9 (November 2005): 1242–64. http://dx.doi.org/10.1016/j.neunet.2005.08.005.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

McGregor. "SNOW AVALANCHE FORECASTING BY DISCRIMINANT FUNCTION ANALYSIS." Weather and Climate 9, no. 2 (1989): 3. http://dx.doi.org/10.2307/44279774.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Nogales, F. J., and A. J. Conejo. "Electricity price forecasting through transfer function models." Journal of the Operational Research Society 57, no. 4 (April 2006): 350–56. http://dx.doi.org/10.1057/palgrave.jors.2601995.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Дисертації з теми "Forecasting function"

1

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.

Повний текст джерела
Анотація:
A fast catchment response usually leads to a shorter lag time, and under these conditions the forecast lead time obtained from a rainfall-runoff model or correlation between upstream and downstream flows may be infeasible for flood warning purposes. Additional lead time can be obtained from short-term quantitative rainfall forecasts that extend the flood warning time and increase the economic viability of a flood forecasting system. For this purpose algorithms which forecasts the quantitative rainfall amounts up to six hours ahead have been developed, based on lumped and distributed approaches. The lumped forecasting algorithm includes the essential features of storm dynamics such as rainband and raincell movements which are represented within the framework of a linear transfer function model. The dynamics of a storm are readily captured by radar data. A space-time rainfall model is used to generate synthetic radar data with known features, e.g. rainband and raincell velocities. This enables the algorithm to be assessed under ideal conditions, as errors are present in observed radar data. The transfer function algorithm can be summarised as follows. The dynamics of the rainbands and raincells are incorporated as inputs into the transfer function model. The algorithm employs simple spatial cross-correlation techniques to estimate the rainband and raincell velocities. The translated rainbands and raincells then form the auxiliary inputs to the transfer function. An optimal predictor based on minimum square error is then derived from the transfer function model, and its parameters are estimated from the auxiliary inputs and observed radar data in real-time using a recursive least squares algorithm. While the transfer-function algorithm forecasts areal rainfalls, a distributed approach which performs rainfall forecasting at a fine spatial resolution (referred to as the advection equation algorithm) is also evaluated in this thesis. The algorithm expresses the space-time rainfall on a Cartesian coordinate system via a partial differential advection equation. A simple explicit finite difference solution scheme is applied to the equation. A comparison of model parameter estimates is undertaken using a square root information filter data processing algorithm, and single-input single-output and multiple-input multiple-output least squares algorithms.
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Burger, S. (Stephan). "Managing the forecasting function within the fast moving consumer goods industry." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53494.

Повний текст джерела
Анотація:
Thesis (MBA)--Stellenbosch University, 2003.
ENGLISH ABSTRACT: Forecasting the future has always been one of the man's strongest desires. The aim to determine the future has resulted in scientifically based forecasting models of human health, behaviour, economics, weather, etc. The main purpose of forecasting is to reduce the range of uncertainty within which management decisions must be made. Forecasts are only effective if they are utilized by those who have decisionmaking authority. Forecasts need to be understood and appreciated by decision makers so that they find their way into management of the firm. Companies still predominantly rely on judgemental forecasting methods, most often on an informal basis. There is a large literature base that point to the numerous biases inherent in judgemental forecasting. Most companies know that their forecasts are incorrect but don't know what to do about it and choose to ignore the issue, hoping that the problem will solve itself. The collaborative forecasting process attempts to use history as a baseline, but supplement current knowledge about specific trends, events and other items. This approach integrates the knowledge and information that exists internally and externally into a single, more accurate forecast that supports the entire supply chain. Demand forecasting is not just a matter of duplicating or predicting history into the future. It is important that one person should lead and manage the process. Accountability needs to be established. An audit on the writer's own organization indicated that no formal forecasting process was present. The company's forecasting process was very political, since values were entered just to add up to the required targets. The real gap was never fully understood. Little knowledge existed regarding statistical analysis and forecasting within the marketing department who is accountable for the forecast. The forecasting method was therefore a top-down approach and never really checked with a bottom up approach. It was decided to learn more about the new demand planning process prescribed by the head office, and to start implementing the approach. The approach is a form of a collaborative approach which aims to involve all stakeholders when generating the forecast, therefore applying a bottom up approach. Statistical forecasting was applied to see how accurate the output was versus that of the old way of forecasting. The statistical forecast approach performed better with product groups where little changed from previous years existed, while the old way performed better where new activities were planned or known by the marketing team. This indicates that statistical forecasting is very important for creating the starting point or baseline forecast, but requires qualitative input from all stakeholders. Statistical forecasting is therefore not the solution to improved forecasting, but rather part of the solution to create robust forecasts.
AFRIKAANSE OPSOMMING: Vooruitskatting van die toekoms was nog altyd een van die mens se grootste begeertes. Die doel om die toekoms te bepaal het gelei tot wiskundige gebaseerde modelle van die mens se gesondheid, gedrag, ekonomie, weer, ens. The hoofdoel van vooruitskatting is om die reeks van risikos te verminder waarbinne bestuur besluite moet neem. Vooruitskattings is slegs effektief as dit gebruik word deur hulle wat besluitnemingsmag het. Vooruitskattings moet verstaan en gewaardeer word deur die besluitnemers sodat dit die weg kan vind na die bestuur van die firma. Maatskappye vertrou nog steeds hoofsaaklik op eie oordeel vooruitskatting metodes, en meestal op 'n informele basis. Daar is 'n uitgebreide literatuurbasis wat daarop dui dat heelwat sydigheid betrokke is by vooruitskattings wat gebaseer is op eie oordeel. Baie organisasies weet dat hulle vooruitskattings verkeerd is, maar weet nie wat daaromtrent te doen nie en kies om die probleem te ignoreer, met die hoop dat die probleem vanself sal oplos. Die geïntegreerde vooruitskattingsproses probeer om die verlede te gebruik as 'n basis, maar voeg huidige kennis rakende spesifieke neigings, gebeurtenisse, en ander items saam. Hierdie benadering integreer die kennis en informasie wat intern en ekstern bestaan in 'n enkele, meer akkurate vooruitskatting wat die hele verskaffingsketting ondersteun. Vraagvooruitskatting is nie alleen 'n duplisering of vooruitskatting van die verlede in die toekoms in nie. Dit is belangrik dat een persoon die proses moet lei en bestuur. Verantwoordelikhede moet vasgestel word. 'n Oudit op die skrywer se organisasie het getoon dat geen formele vooruitskattingsprosesse bestaan het nie. Die maatskappy se vooruitskattingsproses was hoogs gepolitiseerd, want getalle was vasgestel wat in lyn was met die nodige teikens. Die ware gaping was nooit werklik begryp nie. Min kennis was aanwesig rakende statistiese analises en vooruitskatting binne die bemarkingsdepartement wat verantwoordelik is vir die vooruitskatting. Die vooruitskatting is dus eerder gedoen op 'n globale vlak en nie noodwendig getoets deur die vooruitskatting op te bou uit detail nie. Daar is besluit om meer te leer rakende die nuwe vraagbeplanningsproses, wat voorgeskryf is deur hoofkantoor, en om die metode te begin implementeer. Die metode is 'n vorm van 'n geïntegreerde model wat beoog om alle aandeelhouers te betrek wanneer die vooruitskatting gedoen word, dus die vooruitskatting opbou met detail. Statistiese vooruitskatting was toegepas om te sien hoe akkuraat die uitset was teenoor die ou manier van vooruitskatting. Die statistiese proses het beter gevaar waar die produkgroepe min verandering van vorige jare ervaar het, terwyl die ou manier beter gevaar het waar bemarking self die nuwe aktiwiteite beplan het of bewus was daarvan. Dit bewys dat statistiese vooruitskatting baie belangrik is om die basis vooruitskatting te skep, maar dit benodig kwalitatiewe insette van all aandeelhouers. Statistiese vooruitskattings is dus nie die oplossing vir beter vooruitskattings nie, maar deel van die oplossing om kragtige vooruitskattings te skep.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Mosmann, Gabriela. "Axiomatic systemic risk measures forecasting." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/178875.

Повний текст джерела
Анотація:
Neste trabalho, aprofundamos o estudo sobre risco sistêmico via funções de agregação. Consideramos três carteiras diferentes como proxy para um sistema econômico, estas carteiras são consistidas por duas funções de agregação, baseadas em todos as ações do E.U.A, e um índice de mercado. As medidas de risco aplicadas são Value at Risk (VaR), Expected Shortfall (ES) and Expectile Value at Risk (EVaR), elas são previstas através do modelo GARCH clássico unido com nove funções de distribuição de probabilidade diferentes e mais por um método não paramétrico. As previsões são avaliadas por funções de perda e backtests de violação. Os resultados indicam que nossa abordagem pode gerar uma função de agregação adequada para processar o risco de um sistema previamente selecionado.
In this work, we deepen the study of systemic risk measurement via aggregation functions. We consider three different portfolios as a proxy for an economic system, these portfolios are consisted in two aggregation functions, based on all U.S. stocks and a market index. The risk measures applied are Value at Risk (VaR), Expected Shortfall (ES) and Expectile Value at Risk (EVaR), they are forecasted via the classical GARCH model along with nine distribution probability functions and also by a nonparametric approach. The forecasts are evaluated by loss functions and violation backtests. Results indicate that our approach can generate an adequate aggregation function to process the risk of a system previously selected.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Kattekola, Sravanthi. "Weather Radar image Based Forecasting using Joint Series Prediction." ScholarWorks@UNO, 2010. http://scholarworks.uno.edu/td/1238.

Повний текст джерела
Анотація:
Accurate rainfall forecasting using weather radar imagery has always been a crucial and predominant task in the field of meteorology [1], [2], [3] and [4]. Competitive Radial Basis Function Neural Networks (CRBFNN) [5] is one of the methods used for weather radar image based forecasting. Recently, an alternative CRBFNN based approach [6] was introduced to model the precipitation events. The difference between the techniques presented in [5] and [6] is in the approach used to model the rainfall image. Overall, it was shown that the modified CRBFNN approach [6] is more computationally efficient compared to the CRBFNN approach [5]. However, both techniques [5] and [6] share the same prediction stage. In this thesis, a different GRBFNN approach is presented for forecasting Gaussian envelope parameters. The proposed method investigates the concept of parameter dependency among Gaussian envelopes. Experimental results are also presented to illustrate the advantage of parameters prediction over the independent series prediction.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Ford, Debra M. "Forecasting tropical cyclone recurvature using an empirical othogonal [sic] function representation of vorticity fields." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA238489.

Повний текст джерела
Анотація:
Thesis (M.S. in Meteorology and Oceanography)--Naval Postgraduate School, September 1990.
Thesis Advisor(s): Elsberry, Russell L. ; Harr, Patrick A. "September 1990." Description based on title screen as viewed on December 16, 2009. DTIC Identifier(s): EOF (empirical orthogonal functions). Author(s) subject terms: Tropical cyclones, recurvature, empirical orthogonal functions. Includes bibliographical references (p. 73-74). Also available in print.
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Boulougari, Andromachi. "Application of a power-exponential function based model to mortality rates forecasting." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-39921.

Повний текст джерела
Анотація:
De modellering van een wet of mortaliteit heeft een consequente interesse van een grote meerderheid van onderzoekers en vele modellen door de jaren is voorgesteld. The first aim of this thesis is to systematically evaluate a selection of models --- Modified Perks, Heligman-Pollard and Power-exponential --- to determine their relative strengths and weaknesses with regard to forecasting the mortality rate using the Lee-Carter model. Den andre målsætningen er at tilpasse dødelighedsdata ved de selektive modeller fra USA, Sverige og Grækenland ved hjælp af numeriske teknikker til kurvefitting med den ikke-lineære mindst kvadratmetode. The results indicate that the Heligman-Pollard model performs better especially when the phenomenon of the `` accident hump '' occurs during adulthood.
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Weller, Jennifer N. "Bayesian Inference In Forecasting Volcanic Hazards: An Example From Armenia." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000485.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Carriere, Thomas. "Towards seamless value-oriented forecasting and data-driven market valorisation of photovoltaic production." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLM019.

Повний текст джерела
Анотація:
La décarbonation de la production d’électricité à échelle mondiale est un élément de réponse clé face aux pressions exercées par les différents enjeux environnementaux. Par ailleurs, la baisse des coûts de la filière photovoltaïque (PV) ouvre la voie à une augmentation significative de la production PV dans le monde. L’objectif principal de cette thèse est alors de maximiser le revenu d’un producteur d’énergie PV sous incertitude des prix de marché et de la production. Pour cela, un modèle de prévision probabiliste de la production PV à court (5 minutes) et moyen (24 heures) terme est proposé. Ce modèle est couplé à une méthode de participation au marché maximisant l’espérance du revenu. Dans un second temps, le couplage entre une centrale PV et une batterie est étudié, et une analyse de sensibilité des résultats est réalisée pour étudier la rentabilité et le dimensionnement de tels systèmes. Une méthode de participation alternative est proposée, pour lequel un réseau de neurones artificiel apprend à participer avec ou sans batterie au marché de l’électricité, ce qui permet de simplifier le processus de valorisation de l'énergie PV en diminuant le nombre de modèles requis
The decarbonation of electricity production on a global scale is a key element in responding to the pressures of different environmental issues. In addition, the decrease in the costs of the photovoltaic (PV) sector is paving the way for a significant increase in PV production worldwide. The main objective of this thesis is then to maximize the income of a PV energy producer under uncertainty of market prices and production. For this purpose, a probabilistic forecast model of short (5 minutes) and medium (24 hours) term PV production is proposed. This model is coupled with a market participation method that maximizes income expectation. In a second step, the coupling between a PV plant and a battery is studied, and a sensitivity analysis of the results is carried out to study the profitability and sizing of such systems. An alternative participation method is proposed, for which an artificial neural network learns to participate with or without batteries in the electricity market, thus simplifying the process of PV energy valuation by reducing the number of models required
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Schweim, Jarrett Joshua. "Do any of a set of Lower Extremity Functional Assessment tests predict in the incidence of injury among a Cohort of collegiate freshmen football players? A Pilot Study." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1243851951.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Alves, Jose Henrique Gomes de Mattos Mathematics UNSW. "A Saturation-Dependent Dissipation Source Function for Wind-Wave Modelling Applications." Awarded by:University of New South Wales. Mathematics, 2000. http://handle.unsw.edu.au/1959.4/17786.

Повний текст джерела
Анотація:
This study reports on a new formulation of the spectral dissipation source term Sds for wind-wave modelling applications. This new form of Sds features a nonlinear dependence on the local wave spectrum, expressed in terms of the azimuthally integrated saturation parameter B(k)=k^4 F(k). The basic form of this saturation-dependent Sds is based on a new framework for the onset of deep-water wave breaking due to the nonlinear modulation of wave groups. The new form of Sds is succesfully validated through numerical experiments that include exact nonlinear computations of fetch-limited wind-wave evolution and hindcasts of two-dimensional wave fields made with an operational wind-wave model. The newly-proposed form of Sds generates integral spectral parameters that agree more closely with observations when compared to other dissipation source terms used in state-of-the-art wind-wave models. It also provides more flexibility in controlling properties of the wave spectrum within the high wavenumber range. Tests using a variety of wind speeds, three commonly-used wind input source functions and two alternative full-development evolution limits further demonstrate the robustness and flexibility of the new saturation-dependent dissipation source term. Finally, improved wave hindcasts obtained with an implementation of the new form of Sds in a version of the WAM model demonstrate its potential usefulness in operational wind-wave forecasting applications.
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Книги з теми "Forecasting function"

1

Albertson, Kevin. Forecasting with a periodic transfer function model. Salford: University of Salford, Department of Economics, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Albertson, Kevin. Forecasting with a periodic transfer function model. Salford: University of Salford, Department of Economics, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Fildes, Robert. "Forecasting and loss functions". Fontainbleau: INSEAD, 1986.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Ignacio, Rodríguez-Iturbe, ed. Random functions and hydrology. Reading, Mass: Addison-Wesley, 1985.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Bras, Rafael L. Random functions and hydrology. New York: Dover Publications, 1993.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Franke, Richard H. Covariance functions for statistical interpolation. Monterey, California: Naval Postgraduate School, 1986.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Box, George E. P. Time series analysis: Forecasting and control. 4th ed. Hoboken, N.J: John Wiley, 2008.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Box, George E. P. Time series analysis: Forecasting and control. 3rd ed. Englewood Cliffs, N.J: Prentice Hall, 1994.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Box, George E. P. Time series analysis: Forecasting and control. 4th ed. Hoboken, N.J: John Wiley, 2008.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Makridakis, Spyros. Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. Fontainbleau: INSEAD, 1990.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Частини книг з теми "Forecasting function"

1

Romanowicz, Renata J., and Marzena Osuch. "Stochastic Transfer Function Based Emulator for the On-line Flood Forecasting." In Stochastic Flood Forecasting System, 159–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18854-6_10.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Lees, Matthew J. "Advances in Transfer Function Based Flood Forecasting." In Flood Issues in Contemporary Water Management, 421–28. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4140-6_43.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Guerard, John B. "Transfer Function Modeling and Granger Causality Testing." In Introduction to Financial Forecasting in Investment Analysis, 97–143. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5239-3_5.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Aliverti, Emanuele, Daniele Durante, and Bruno Scarpa. "Projecting Proportionate Age–Specific Fertility Rates via Bayesian Skewed Processes." In Developments in Demographic Forecasting, 89–103. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42472-5_5.

Повний текст джерела
Анотація:
Abstract Fertility rates show dynamically–varying shapes when modeled as a function of the age at delivery. We incorporate this behavior under a novel Bayesian approach for dynamic modeling of proportionate age–specific fertility rates via skewed processes. The model assumes a skew–normal distribution for the age at the moment of childbirth, while allowing the location and the skewness parameters to evolve in time via Gaussian processes priors. Posterior inference is performed via Monte Carlo methods, leveraging results on unified skew–normal distributions. The proposed approach is illustrated on Italian age–specific fertility rates from 1991 to 2014, providing forecasts until 2030.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Isha, Akash Singh Chaudhary, and D. K. Chaturvedi. "Effects of Activation Function and Input Function of ANN for Solar Power Forecasting." In Advances in Data and Information Sciences, 329–42. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0694-9_31.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Gontar, Zbigniew, George Sideratos, and Nikos Hatziargyriou. "Short-Term Load Forecasting Using Radial Basis Function Networks." In Methods and Applications of Artificial Intelligence, 432–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24674-9_45.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Romanenko, Alexey. "Aggregation of Adaptive Forecasting Algorithms Under Asymmetric Loss Function." In Statistical Learning and Data Sciences, 137–46. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17091-6_9.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Kumar, Kriti, Angshul Majumdar, M. Girish Chandra, and A. Anil Kumar. "Transform Learning Based Function Approximation for Regression and Forecasting." In Advanced Analytics and Learning on Temporal Data, 14–25. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39098-3_2.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Šimpach, Ondřej, and Petra Dotlačilová. "Age-Specific Death Rates Smoothed by the Gompertz–Makeham Function and Their Application in Projections by Lee–Carter Model." In Time Series Analysis and Forecasting, 233–45. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28725-6_18.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Basellini, Ugofilippo, and Carlo Giovanni Camarda. "A Three-Component Approach to Model and Forecast Age-at-Death Distributions." In Developments in Demographic Forecasting, 105–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42472-5_6.

Повний текст джерела
Анотація:
Abstract Mortality forecasting has recently received growing interest, as accurate projections of future lifespans are needed to ensure the solvency of insurance and pension providers. Several innovative stochastic methodologies have been proposed in most recent decades, the majority of them being based on age-specific mortality rates or on summary measures of the life table. The age-at-death distribution is an informative life-table function that provides readily available information on the mortality pattern of a population, yet it has been mostly overlooked for mortality projections. In this chapter, we propose to analyse and forecast mortality developments over age and time by introducing a novel methodology based on age-at-death distributions. Our approach starts from a nonparametric decomposition of the mortality pattern into three independent components corresponding to Childhood, Early-Adulthood and Senescence, respectively. We then model the evolution of each component-specific death density with a relational model that associates a time-invariant standard to a series of observed distributions by means of a transformation of the age axis. Our approach allows us to capture mortality developments over age and time, and forecasts can be derived from parameters’ extrapolation using standard time series models. We illustrate our methods by estimating and forecasting the mortality pattern of females and males in two high-longevity countries using data of the Human Mortality Database. We compare the forecast accuracy of our model and its projections until 2050 with three other forecasting methodologies.
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Forecasting function"

1

Cao, Guozhong, Haixia Guo, Chengye Zhang, Hongxun Liu, and Qinghai Li. "Function evolution and forecasting for product innovation." In 2010 IEEE International Conference on Management of Innovation & Technology. IEEE, 2010. http://dx.doi.org/10.1109/icmit.2010.5492843.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Kiani, Hashir Moheed, and Xiao-Jun Zeng. "A Function-on-Function Linear Regression Approach for Short-Term Electric Load Forecasting." In 2019 IEEE Texas Power and Energy conference (TPEC). IEEE, 2019. http://dx.doi.org/10.1109/tpec.2019.8662147.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Manusov, V. Z., and K. N. Boyko. "Construction of the membership function for fuzzy forecasting models." In 2014 12th International Conference on Actual Problems of Electronics Instrument Engineering (APEIE). IEEE, 2014. http://dx.doi.org/10.1109/apeie.2014.7040796.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Chien, Shan Heng, Zoilo S. Roldan, and Roger J. Lee. "Forecasting Reliability as a Function of Preemptive Infrastructure Replacement." In 2007 IEEE Power Engineering Society General Meeting. IEEE, 2007. http://dx.doi.org/10.1109/pes.2007.386008.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Kuo, R. J., Tung-Lai Hu, and Zhen-Yao Chen. "Application of Radial Basis Function Neural Network for Sales Forecasting." In 2009 International Asia Conference on Informatics in Control, Automation and Robotics (CAR). IEEE, 2009. http://dx.doi.org/10.1109/car.2009.97.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Dong, Jin, Teja Kuruganti, and Seddik M. Djouadi. "Very short-term photovoltaic power forecasting using uncertain basis function." In 2017 51st Annual Conference on Information Sciences and Systems (CISS). IEEE, 2017. http://dx.doi.org/10.1109/ciss.2017.7926158.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Shakya, Suja, Hongchun Yuan, Xinjun Chen, and Liming Song. "Application of radial basis Function Neural Network for fishery forecasting." In 2011 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, 2011. http://dx.doi.org/10.1109/csae.2011.5952682.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Lia, Xue-mei, and Keith W. Hipel. "Forecasting Model of Grey Numbers with Triangular Whitenization Weight Function." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.353.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Anggraeni, Wiwik, Dina Nandika, Faizal Mahananto, Yeyen Sudiarti, and Cut Alna Fadhilla. "Diphtheria Case Number Forecasting using Radial Basis Function Neural Network." In 2019 3rd International Conference on Informatics and Computational Sciences (ICICoS). IEEE, 2019. http://dx.doi.org/10.1109/icicos48119.2019.8982403.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Lukianets, O., O. Obodovskyi, V. Grebin, and O. Pochaievets. "TIME SERIES ANALYSIS AND FORECAST ESTIMATES FOR THE MEAN ANNUAL RIVERINE WATER RUNOFF WITHIN THE UKRAINIAN PART OF THE PRUT AND SIRET BASINS." In XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management. Nika-Tsentr, 2020. http://dx.doi.org/10.15407/uhmi.conference.01.15.

Повний текст джерела
Анотація:
The systematization, generalization, estimation of the variability of time series of the mean annual water runoff of rivers in of the Prut and Siret basins has been carried out, and its cyclic structure has been revealed. For this purpose, a database of average annual discharges water with 12 of hydrological observing stations on the rivers in of the Prut and Siret basins from the beginning of observations to 2015 have been created. Number of years under observation by the annual runoff values for river Prut near city of Chernivtsi is 121. Their representativeness and homogeneity for practical calculations has been evaluated. To identify and formalize the cyclic structure of time series of the mean annual water runoff of rivers in of the Prut and Siret basins used the methods of mathematical statistics and theory of random functions: a function of mathematical expected value; a function of dispersion values or standard deviation; probability distribution function; autocorrelation function. Also have been involved different of the standard mathematical criteria (criteria homogeneity, criteria of the series and of the longest series), integral curves of the differences. As a result, the structure of cyclic oscillations is revealed of the mean annual water runoff of rivers in the Prut and Siret basins and that is what made it possible to provide forecast estimates until 2050.
Стилі APA, Harvard, Vancouver, ISO та ін.

Звіти організацій з теми "Forecasting function"

1

Poppeliers, Christian, Katherine Aur, and Leiph Preston. Predicting Atmospheric Green's Functions using the Weather Research and Forecasting Model. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1761090.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

Повний текст джерела
Анотація:
The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Poppeliers, Christian, Katherine Anderson Aur, and Leiph Preston. Infrasound Predictions Using the Weather Research and Forecasting Model: Atmospheric Green's Functions for the Source Physics Experiments 1-6. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1426618.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Також вас можуть зацікавити розширені добірки на тему "Forecasting function" для конкретних типів джерел:
Статті в журналах Дисертації Книги
Ми пропонуємо знижки на всі преміум-плани для авторів, чиї праці увійшли до тематичних добірок літератури. Зв'яжіться з нами, щоб отримати унікальний промокод!

До бібліографії