Search Results - "Hui, Yongyong"

Multi-phase batch process monitoring based on multiway weighted global neighborhood preserving embedding method by Hui, Yongyong, Zhao, Xiaoqiang

“…•The process is divided into different operation phases, and it is easy to carry out statistical analysis for each phase.•Global and local structures are fully…”
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Multiway dynamic nonlinear global neighborhood preserving embedding method for monitoring batch process by Hui, Yongyong, Zhao, Xiaoqiang

“…Aiming at the dynamic and nonlinear characteristics of batch process, a multiway dynamic nonlinear global neighborhood preserving embedding algorithm is…”
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Quality-related batch process monitoring based on multi-way orthogonal signal correction enhanced total principal component regression by Zhang, Yan, Zhao, Xiaoqiang, Hui, Yongyong, Cao, Jie

“…Batch process quality-related fault detection is necessary for keeping operation safety and quality consistency. However, the process variables have a weak…”
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Sparse representation preserving embedding based on extreme learning machine for process monitoring by Yongyong, Hui, Xiaoqiang, Zhao

“…Extreme learning machine (ELM) is a fast learning mechanism used in many domains. Unsupervised ELM has improved to extract nonlinear features. A nonlinear…”
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Batch process monitoring based on global enhanced multiple neighborhoods preserving embedding by Yao, Hongjuan, Zhao, Xiaoqiang, Li, Wei, Hui, Yongyong

“…Batch process generally has varying dynamic characteristic that causes low fault detection rate and high false alarm rate, and it is necessary and urgent to…”
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Batch process monitoring based on WGNPE–GSVDD related and independent variables by Hui, Yongyong, Zhao, Xiaoqiang

“…In many batch processes, there are related or independence relationships among process variables. The traditional monitoring method usually carries out a…”
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MGNPE-LICA algorithm for fault diagnosis of batch process by Xiaoqiang, Zhao, Tao, Wang, Yongyong, Hui

“…Batch production process data usually contains mixture ingredients of the Gaussian and non‐Gaussian distribution. Traditional monitoring methods require data…”
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Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management by Wang, Jiyue, Elbagory, Mohssen, He, Yingdui, Zhang, Xu, Hui, Yongyong, Eissa, Mamdouh A., Ding, Zheli, El-Nahrawy, Sahar, Omara, Alaa El-Dein, Zoghdan, Medhat G., Kheir, Ahmed M. S.

“…The continuous addition of phosphorus (P) fertilizers above plant requirements increases P loss risks, especially if such fertilization practices continue…”
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An adaptive imbalance robust graph embedding broad learning system fault diagnosis for imbalanced batch processes data by Liu, Kai, Zhao, Xiaoqiang, Hui, Yongyong

“…Modern batch processes develop toward higher levels, and devices usually work at normal conditions with generally very few faults. Therefore, fewer fault data…”
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Nonlinear multiphase batch process monitoring and quality prediction using multi-way concurrent locally weighted projection regression by Zhang, Yan, Cao, Jie, Zhao, Xiaoqiang, Hui, Yongyong

“…The batch process has the characteristics of nonlinear and multiphase due to variation operation conditions. Nonlinear and multiphase modeling of the batch…”
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An adaptive strategy for time‐varying batch process fault prediction based on stochastic configuration network by Liu, Kai, Zhao, Xiaoqiang, Hui, Yongyong, Jiang, Hongmei

“…Fault prediction ensures safe and stable production, and cuts maintenance costs. Due to the changing operating conditions that lead to the changes in the…”
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Quality-related fault monitoring for multi-phase batch process based on multiway weighted elastic network by Yao, Hongjuan, Zhao, Xiaoqiang, Li, Wei, Hui, Yongyong

“…A quality-related fault monitoring method of multi-phase batch process based on multiway weighted elastic network is proposed in this paper. Firstly, to make…”
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Channel attention generative adversarial network for super-resolution of glioma magnetic resonance image by Song, Zhaoyang, Qiu, Defu, Zhao, Xiaoqiang, Lin, Dongmei, Hui, Yongyong

“…•Developed the channel attention generative adversarial network.•Designed a novel residual dense block.•Adopt a relative average discriminator to replace the…”
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Progressive back-projection network for COVID-CT super-resolution by Song, Zhaoyang, Zhao, Xiaoqiang, Hui, Yongyong, Jiang, Hongmei

“…•Developed a progressive back-projection network (PBPN) for COVID-CT super-resolution, which improves the performance of COVID-CT super-resolution.•Designed an…”
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Variational autoencoder based on distributional semantic embedding and cross-modal reconstruction for generalized zero-shot fault diagnosis of industrial processes by Mou, Miao, Zhao, Xiaoqiang, Liu, Kai, Hui, Yongyong

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Nonlinear Quality‐Related Fault Detection Using Neighborhood Embedding Neural Orthogonal Mapping Algorithm for Batch Process by Liu, Kai, Zhao, Xiaoqiang, Hui, Yongyong, Jiang, Hongmei

“…Quality‐related fault detection has become a hot research topic in recent years. It is not reliable to measure quality‐related relationships only by mutual…”
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Siamese DeNPE network framework for fault detection of batch process by Liu, Kai, Zhao, Xiaoqiang, Mou, Miao, Hui, Yongyong

“…In batch processes, it is crucial to ensure safe production by fault detection. However, the long batch duration, limited runs, and strong nonlinearity of the…”
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Soft sensor model for nonlinear dynamic industrial process based on GraphSAGE-IMATCN by Tuo, Benben, Zhao, Xiaoqiang, Sun, Kaiwen, Liu, Kai, Hui, Yongyong

“…Industrial process data are closely related to production conditions and are essentially complex time series with high nonlinearity and dynamics. To solve the…”
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Multi‐stage fusion regression network for quality prediction of batch process by Yao, Hongjuan, Zhao, Xiaoqiang, Li, Wei, Hui, Yongyong

“…Abstract In most batch processes, the correlations of process variables present multi‐stage characteristic as the process progress and operating conditions…”
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Parallel Alternating Iterative Optimization for Cardiac Magnetic Resonance Image Blind Super-Resolution by Song, Zhaoyang, Qiu, Defu, Zhao, Xiaoqiang, Liu, Ruijuan, Hui, Yongyong, Jiang, Hongmei

“…Cardiac magnetic resonance imaging (CMRI) super-resolution (SR) reconstruction technology can enhance the resolution and quality of CMRI, providing experts…”
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