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Akademický článek

Research Advances in Mongolian Gerbil Models of Cerebral Ischemia and Auditory Impairment

Autor: ZHANG Zishan, WU Ying, LI Feiyang, DU Xiaoyan

Publikováno v: Shiyan dongwu yu bijiao yixue, Vol 44, Iss 4, Pp 419-427 (2024)

The Mongolian gerbil currently used as laboratory animals worldwide all originates from China. As early as the 1930s, wild Mongolian gerbils were domesticated and introduced into medical research. Today, they have become recognized multifunctional la

Externí odkaz: https://doaj.org/article/e5f82d21ca8e4509a7f546429542e131

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Improved Adaboost Algorithm for Web Advertisement Click Prediction Based on Long Short-Term Memory Networks

Autor: Yu, Qixuan, Tang, Xirui, Li, Feiyang, Cao, Zinan

This paper explores an improved Adaboost algorithm based on Long Short-Term Memory Networks (LSTMs), which aims to improve the prediction accuracy of user clicks on web page advertisements. By comparing it with several common machine learning algorit

Externí odkaz: http://arxiv.org/abs/2408.05245

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Regression prediction algorithm for energy consumption regression in cloud computing based on horned lizard algorithm optimised convolutional neural network-bidirectional gated recurrent unit

Autor: Li, Feiyang, Cao, Zinan, Yu, Qixuan, Tang, Xirui

For this paper, a prediction study of cloud computing energy consumption was conducted by optimising the data regression algorithm based on the horned lizard optimisation algorithm for Convolutional Neural Networks-Bi-Directional Gated Recurrent Unit

Externí odkaz: http://arxiv.org/abs/2407.14575

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Optimising Random Forest Machine Learning Algorithms for User VR Experience Prediction Based on Iterative Local Search-Sparrow Search Algorithm

Autor: Tang, Xirui, Li, Feiyang, Cao, Zinan, Yu, Qixuan, Gong, Yulu

In this paper, an improved method for VR user experience prediction is investigated by introducing a sparrow search algorithm and a random forest algorithm improved by an iterative local search-optimised sparrow search algorithm. The study firstly co

Externí odkaz: http://arxiv.org/abs/2406.16905

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