Parallel Algorithm for Time Series Based Forecasting on OTIS-Mesh
نویسندگان
چکیده
Forecasting plays an important role in business, technology, climate and many others. As an example, effective forecasting can enable an organization to reduce lost sales, increase profits and more efficient production planning. In this paper, we present a parallel algorithm for short term forecasting based on a time series model called weighted moving average. Our algorithm is mapped on OTIS-mesh, a popular model of optoelectronic parallel computers.. Scalability of the algorithm is also discussed.
منابع مشابه
Improved Parallel Algorithm for Time Series Based Forecasting Using OTIS-Mesh
Forecasting always plays an important role in business, technology and many others and it helps organizations to increase profits, reduce lost sales and more eff icient production planning. A parallel algorithm for forecasting reported recently on OTIS-Mesh[9]. This parallel algorithm requires 5( – 1) electronic steps and 4 optical steps. In this paper we present an improved parallel algorithm ...
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