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The prediction of time series is one of the most important scientific fields in information sciences (for example, in the development of AI). One of the most difficult tasks is how to reduce the time of building a prediction. In this paper the efficient method of calculating universal-coding-based predictors is presented. This approach allows to calculate the Krichevsky predictor and similar ones...
We propose application of method, based on notion of computer capacity, for evaluating the performance of computer systems. Computer capacity is based on the number of different tasks that can be executed in a given time. This characteristic determined only by the computer architecture, and it can be easily computed at the design stage and used for optimizing architectural decisions.
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