CRUDE OIL PRICE FORECASTING WITH TEI@I METHODOLOGY ∗

By WangShouyang, YuLean, Kin Keung Lai. 2005

160 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ffefe88374916b676afd626e83f9598330d57b75

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1. Ling Tang
2. Zishu Wang

Citations in the corpus

• Evolutionary Neural Network model for West Texas Intermediate crude oil price prediction (2015, unknown): “[29] BP Prediction of WTI crude o”
• A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting (2015, methodology): “As for hybrid models, under the promising concept of ‘‘divide and conquer’’ (or ‘‘decomposition and ensemble’’) [19], a series of decomposition–ensemble learning paradigms have currently been developed and become a predominant type for crude oil price analysis and forecasting.”