Search Results - "Song, Jiuxiang"

EEGGAN-Net: enhancing EEG signal classification through data augmentation by Song, Jiuxiang, Zhai, Qiang, Wang, Chuang, Liu, Jizhong

“…Emerging brain-computer interface (BCI) technology holds promising potential to enhance the quality of life for individuals with disabilities. Nevertheless,…”
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Prediction of yarn strength based on an expert weighted neural network optimized by particle swarm optimization by Zhang, Baowei, Song, Jiuxiang, Zhao, Suna, Jiang, Hao, Wei, Jingdian, Wang, Yonghua

“…Aiming at solving the problem that existing artificial neural networks (ANNs) still have low accuracy in predicting yarn strength, this study combines…”
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PSO-DE-Based Regional Scheduling Method for Shared Vehicles by Baowei Zhang, Song, Jiuxiang, Wang, Yonghua

“…Numerous parking spots are generated during the use of shared cars. However, in the scheduling process, if only the condition of satisfying the number of…”
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The state prediction method of the silk dryer based on the GA-BP model by Jiang, Hao, Yu, Zegang, Wang, Yonghua, Zhang, Baowei, Song, Jiuxiang, Wei, Jingdian

“…Considering the under-maintenance and over-maintenance of existing equipment maintenance methods, this paper studies a Condition Based Maintenance method for…”
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Yarn Hairiness Prediction by Generalized Regression Neural Network based on Harris Hawk Optimization by Song, Jiuxiang, Fan, Tingting

“…Yarn hairiness is an important indicator of yarn quality. It affects not only the quality of yarn but also the woven and knitted performance of yarn and the…”
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Yarn unevenness prediction using generalized regression neural network under various optimization algorithms by Jiang, Hao, Song, Jiuxiang, Zhang, Baowei, Wang, Yonghua

“…Unevenness is one of the important parameters for evaluating yarn quality, but the current prediction accuracy of yarn unevenness is low. One of the important…”
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Teaching System of Hydraulic Transmission Combined with Virtual Reality Technology by Song, Jiuxiang, Chen, Zhuoxian, Li, Yi, Liu, Jizhong

“…Traditional hydraulic drive experiments present a number of challenges. During the hydraulic transmission experiment, the equipment is easily damaged and must…”
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Study of Yarn Quality Prediction Model based on Fuzzy Comprehensive Evaluation by Wang, Yonghua, Song, Jiuxiang, Fan, Tingting, Zhang, Baowei, Jiang, Hao, Wang, Chuang

“…Yarn quality prediction is a complex nonlinear MIMO (Multiple-Input Multiple-Output) problem. In this paper, a fuzzy comprehensive evaluation model is…”
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Yarn Strength CV Prediction Using Principal Component Analysis and Automatic Relevance Determination on Bayesian Platform by Zhang, Baowei, Song, Jiuxiang, Wang, Yonghua, Wei, Jingdian, Jiang, Hao, Feng, Lizeng

“…Faced with the problems of few factory data samples, numerous parameters, and strong collinearity between parameters, this paper proposes a Bayesian algorithm…”
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ISMOTE: A More Accurate Alternative for SMOTE by Song, Jiuxiang, Liu, Jizhong

“…Classification models trained on imbalanced datasets tend to be biased towards the majority category, resulting in reduced accuracy for minority categories. A…”
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Multi-fidelity model based on synthetic minority over-sampling technique by Song, Jiuxiang, Liu, Jizhong

“…Oversampling is a commonly employed technique to address class imbalance problems by equalizing the sizes of different data classes through the addition of the…”
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Prediction of yarn unevenness based on BMNN by Jiang, Hao, Song, Jiuxiang, Zhang, Baowei, Zhao, Suna, Wang, Yonghua

“…With the continuous development of deep learning, due to the complexity of the deep neural network structure and the limitation of training time, some scholars…”
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