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PRIMO: Progressive Induction for Multi-hop Open Rule Generation

Autor: Liu, Jianyu, Bi, Sheng, Qi, Guilin

Open rule refer to the implication from premise atoms to hypothesis atoms, which captures various relations between instances in the real world. Injecting open rule knowledge into the machine helps to improve the performance of downstream tasks such

Externí odkaz: http://arxiv.org/abs/2411.01205

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A Combination Model Based on Sequential General Variational Mode Decomposition Method for Time Series Prediction

Autor: Chen, Wei, Yang, Yuanyuan, Liu, Jianyu

Accurate prediction of financial time series is a key concern for market economy makers and investors. The article selects online store sales and Australian beer sales as representatives of non-stationary, trending, and seasonal financial time series

Externí odkaz: http://arxiv.org/abs/2406.03157

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A Combination Model for Time Series Prediction using LSTM via Extracting Dynamic Features Based on Spatial Smoothing and Sequential General Variational Mode Decomposition

Autor: Liu, Jianyu, Chen, Wei, Zhang, Yong, Chen, Zhenfeng, Wan, Bin, Hu, Jinwei

In order to solve the problems such as difficult to extract effective features and low accuracy of sales volume prediction caused by complex relationships such as market sales volume in time series prediction, we proposed a time series prediction met

Externí odkaz: http://arxiv.org/abs/2406.03144

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