EVALUATION OF STOCK OPTION PRICES BY USING THE PREDICTION OF FRACTAL TIME-SERIES This report deals with the prediction method for the time-series bearing fractal geometry. The method is applied to the forecast of stock price and option premium, and the results show better performance of investment...
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Definition: A subset of machine learning that uses neural networks with multiple layers (hence "deep") to model complex patterns in data. Key Concept: Effective for tasks like image recognition, natural language processing, and autonomous systems. Examples:Convolutional Neural Networks (CNNs)for imag...
https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-pyth Conv1d-WaveNet-Forecast Stock price: wavenet 模型预测股票价格 https://www.kaggle.com/bhavinmoriya/conv1d-wavenet-forecast-stock-price towardsd...
1.iTransformer: InvertedTransformers Are Effective for Time Series Forecastina 2.Pathformer: Multi- Scale Transformers With Adaptive Pathways For Time Series Forecasting 3.SCALEFORMER: ITERATIVE MULTI-SCALE REFINING TRANSFORMERS FOR TIME SERIESFORECASTING ...
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模型比对结果表明,该研究提出的两个物理约束模型omega-GNN和omega-EGNN相较于数值模式,显著提升各分类降水预报技巧,同时其性能优于目前主流的无物理约束深度学习模型(如U-NET,3D-CNN等)。 图4 物理约束的omega-GNN模型 图5 各模型(a)TS评分,(b-g)相对...
From CNN’s Hira Humayun and Maija-Lisa Ehlinger Damage is seen from Hurricane Dorian on Abaco Island on September 3, 2019 in the Bahamas. The HeadKnowles Foundation via Getty Images The Bahamas have been pummelled by the hurricane, and as officials start to take stock of the damage, other...