Výsledky vyhledávání

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SNAP: Stopping Catastrophic Forgetting in Hebbian Learning with Sigmoidal Neuronal Adaptive Plasticity

Autor: Xu, Tianyi, Zheng, Patrick, Liu, Shiyan, Lyu, Sicheng, Prémont-Schwarz, Isabeau

Artificial Neural Networks (ANNs) suffer from catastrophic forgetting, where the learning of new tasks causes the catastrophic forgetting of old tasks. Existing Machine Learning (ML) algorithms, including those using Stochastic Gradient Descent (SGD)

Externí odkaz: http://arxiv.org/abs/2410.15318

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Hidden high-risky states identification from routine urban traffic

Autor: Liu, Shiyan, Bai, Mingyang, Guo, Shengmin, Gao, Jianxi, Sun, Huijun, Gao, Ziyou, Li, Daqing

One of the core risk management tasks is to identify hidden high-risky states that may lead to system breakdown, which can provide valuable early warning knowledge. However, due to high dimensionality and nonlinear interaction embedded in large-scale

Externí odkaz: http://arxiv.org/abs/2407.20478

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Akademický článek

Application of SRNN-GRU in Photovoltaic power Forecasting

Autor: Liu Shiyan, Hao Xiaoguang, Meng Zhengji, Li Jianfeng, Cui Tongfei, Wei Le

Publikováno v: E3S Web of Conferences, Vol 256, p 02001 (2021)

Short-term photovoltaic power forecasting is of great significance for maintaining the security and stability of the power grid and coordinating the utilization of resources. As one of the Deep Learning Methods, Recurrent Neural Network (RNN) is wide

Externí odkaz: https://doaj.org/article/cc1f46bda9674e4ebb8f14b6df44d96e

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Akademický článek

Location planning of distributed energy stations based on improved P-median model

Autor: Meng Zhengji, Hao Xiaoguang, Liu Shiyan, Li Jianfeng

Publikováno v: E3S Web of Conferences, Vol 256, p 02009 (2021)

The integrated energy system creates the possibility for the interconnection and coordination of different energy sources, and is an effective means to improve the energy use of the system, increase energy efficiency, and reduce environmental polluti

Externí odkaz: https://doaj.org/article/41711cdeed3d4422bdc48867c55ab892

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Blazar constraints on neutrino-dark matter scattering

Autor: Cline, James M., Gao, Shan, Guo, Fangyi, Lin, Zhongan, Liu, Shiyan, Puel, Matteo, Todd, Phillip, Xiao, Tianzhuo

Neutrino emission in coincidence with gamma rays has been observed from the blazar TXS 0506+056 by the IceCube telescope. Neutrinos from the blazar had to pass through a dense spike of dark matter (DM) surrounding the central black hole. The observat

Externí odkaz: http://arxiv.org/abs/2209.02713

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