Timeseries forecasting
This dataset provides realistic Internet of Things (IoT) traffic time-series data generated using the novel Tiered Markov-Modulated Stochastic Process (TMMSP) framework. The dataset captures the unique temporal dynamics and stochastic characteristics of three distinct IoT applications: smart city, eHealth, and smart factory systems. Each application's traffic pattern reflects real-world behaviors including human-machine correlation (HMC), sudden data bursts, and application-specific seasonality patterns.
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The dataset contains information on the demand for milk in liters for a milk society over a certain period of time. The data is organized based on the week number and year number, providing a time-series view of the milk demand. The purpose of the dataset may be to analyze trends in milk demand over time, identify seasonal patterns, or inform production and distribution decisions for the milk society. Further analysis and exploration of the dataset can provide valuable insights into the milk industry and consumer behavior related to milk consumption
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