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The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy of different time series forecasting methods. They are organized by teams led by forecasting researcher Spyros Makridakis and were first held in 1982. [1] [2] [3] [4]
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The Global Energy Forecasting Competition (GEFCom) is a competition conducted by a team led by Dr. Tao Hong that invites submissions around the world for forecasting energy demand. [1] GEFCom was first held in 2012 on Kaggle , [ 2 ] and the second GEFCom was held in 2014 on CrowdANALYTIX.
JaamSim is a fast and scalable discrete-event simulation software that includes a drag-and-drop user interface, interactive 3D graphics, input and output processing and model development tools and editors. [18] "Out of all the OS DES projects we reviewed, JaamSim is the one with the most impressive 3D user interface that can compete against ...
ARIMA univariate and multivariate models can be used in forecasting a company's future cash flows, with its equations and calculations based on the past values of certain factors contributing to cash flows. Using time-series analysis, the values of these factors can be analyzed and extrapolated to predict the future cash flows for a company.
CSV and PDF Natural language processing, QnA 2021 The Atticus Project: Vietnamese Image Captioning Dataset (UIT-ViIC) Vietnamese Image Captioning Dataset 19,250 captions for 3,850 images CSV and PDF Natural language processing, Computer vision 2020 [112] Lam et al. Vietnamese Names annotated with Genders (UIT-ViNames)
Forecast either to existing data (static forecast) or "ahead" (dynamic forecast, forward in time) with these ARMA terms. Apply the reverse filter operation (fractional integration to the same level d as in step 1) to the forecasted series, to return the forecast to the original problem units (e.g. turn the ersatz units back into Price).
The Weather Research and Forecasting (WRF) Model [1] (/ ˈ w ɔːr f /) is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. NWP refers to the simulation and prediction of the atmosphere with a computer model, and WRF is a set of software for this.