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IMPACT2020 | Your Open-Source Machine Learning Tool Kit – Luiz Eduardo Gazola de Souza & Joao Natalino De Oliveira
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An overloaded computer must finish what it starts and not start what will fail or hang. Our presenter developed a congestion control algorithm that manages overload with its unique formulation of Exponential Smoothing forecasting.
Siemens filed for exclusive rights to this technique in 2003 and obtained US patent US7301903B2 in 2007 with this author, an employee at the time of the filing, the sole inventor. A computer program, written in C language, which exercises the methodology is contained in the companion paper to this talk.
Key Takeaways:
1. This unique Exponential Smoothing algorithm is a complete package ready for implementation.
2. The algorithm is a generic time series forecasting tool adaptable to a broad range of tracking and prediction situations.
3. Exponential Smoothing is better than a Moving Average because it requires less stored data and gives more weight to more recent
data.
4. Two Exponential Smoothing model issues are resolved, and two algorithm implementation requirements are met.
5. A detailed understanding of the algorithm’s math is unnecessary because a runnable computer program listed in the companion paper
performs the computations.
Presented By
James Brady, Capacity Planner
Carson City, Nevada USA
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