Experimental investigation of the efficiency of universal measures based forecasting methods

P. Pristavka, Boris Ryabko
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Abstract

We describe and experimentally investigate a method to construct forecasting algorithms for stationary and ergodic processes based on universal measures (or so-called universal data compressors). Using the time series of solar activity indices as a research target, we show that the quality of the predictions is higher than that of known methods forecasts.
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基于通用测度的预测方法有效性的实验研究
我们描述并实验研究了一种基于通用度量(或所谓的通用数据压缩器)构建平稳和遍历过程预测算法的方法。以太阳活动指数时间序列为研究对象,结果表明该方法的预测质量高于已知方法的预测质量。
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