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Input Variable Selection for Time Series Forecasting with Artificial Neural Networks: An Empirical Evaluation across Varying Time Series Frenquencies.

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Figure

table 2-111. About 40% o f the papers discuss univariate tim e series forecasting problems and only 7 papers (6.8%) examine both possible forms
Table 2-V: N u m b er o f papers per tim e g ran u larity
Table 2-VI: Number of tim e series Min 1.0 10% 1.0 20% 1.0 30% 1.0 QJ '-t—' 40% 1.0 c QJ u 50% 2.0 1— QJ 60% 3.0 Q
Table 2-XI: Error types in ANN lite ra tu re
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