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  2. Technology forecasting - Wikipedia

    en.wikipedia.org/wiki/Technology_forecasting

    [11] [12] [13] Normative methods of technology forecasting—like the relevance trees, morphological models, and mission flow diagrams—are also commonly used. Delphi method is widely used in technology forecasts because of its flexibility and convenience. However, the requirement on reaching consensus is a possible disadvantage of Delphi method.

  3. Delphi method - Wikipedia

    en.wikipedia.org/wiki/Delphi_method

    e. The Delphi method or Delphi technique (/ ˈdɛlfaɪ / DEL-fy; also known as Estimate-Talk-Estimate or ETE) is a structured communication technique or method, originally developed as a systematic, interactive forecasting method that relies on a panel of experts. [1][2][3][4][5] Delphi has been widely used for business forecasting and has ...

  4. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]

  5. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis. Prediction is a similar but more general term.

  6. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    Box–Jenkins method. In time series analysis, the Box–Jenkins method, [1] named after the statisticians George Box and Gwilym Jenkins, applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series model to past values of a time series.

  7. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    In statistics and econometrics, and in particular in time series analysis, an autoregressive integrated moving average (ARIMA) model is a generalization of an autoregressive moving average (ARMA) model. To better comprehend the data or to forecast upcoming series points, both of these models are fitted to time series data.

  8. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    The Bass model or Bass diffusion model was developed by Frank Bass. It consists of a simple differential equation that describes the process of how new products get adopted in a population. The model presents a rationale of how current adopters and potential adopters of a new product interact. The basic premise of the model is that adopters can ...

  9. Ensemble forecasting - Wikipedia

    en.wikipedia.org/wiki/Ensemble_forecasting

    Ensemble forecasting is a form of Monte Carlo analysis. The multiple simulations are conducted to account for the two usual sources of uncertainty in forecast models: (1) the errors introduced by the use of imperfect initial conditions, amplified by the chaotic nature of the evolution equations of the atmosphere, which is often referred to as ...