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Akademický článek

Amino acid characteristics and nutritional evaluation of Flammulina filiformis protoplast hybrid strains

Autor: LU Huan, LIU Jianyu, SHANG Xiaodong, YANG Hui, WU Yansha, WANG Ruijuan

Publikováno v: Shipin yu jixie, Vol 39, Iss 8, Pp 25-33,41 (2023)

Objective: This study aimed to investigate the quality differences among different hybrid enoki mushrooms （Flammulina filiformis） strains and breed new strains with high quality. Methods: Two different protoplast monocytes of yellow enoki mushroo

Externí odkaz: https://doaj.org/article/a025f421c6894b43885f31973b5a80f2

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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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Akademický článek

Bayesian regularized NAR neural network based short-term prediction method of water consumption

Autor: Liu Jianyu, Zhao Linxue, Mao Yanlong

Publikováno v: E3S Web of Conferences, Vol 118, p 03024 (2019)

With the continuous construction of urban water supply infrastructure, it is extremely urgent to change the management mode of water supply from traditional manual experience to modern and efficient means. The water consumption forecast is the premis

Externí odkaz: https://doaj.org/article/d1cca897213241c896f41da3f0bb0a96

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