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第36届中国控制会议

作者： Hua Xie Min Ding Luefeng Chen Jianqi An Zhangbing Chen Min Wu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Accurate short-term wind power prediction can improve the trade and the dispatch level of wind *** predict the short-term wind power,we investigated the empirical mode decomposition（EMD） of numerical weather prediction（NWP） and genetic algorithm（GA） optimization of support vector regression（SVR）.First,the wind speed data from NWP is decomposed into the EMD components,including multiple intrinsic mode functions（IMFs） and one ***,a genetic algorithmsupport vector regression model（GA-SVR） is used to build models of all ***,the prediction results of all components are integrated,which as input of wind-power curve for obtain the predicted value of wind *** order to validate the proposed method,one real-world dataset was used for model training and testing,and the results show that the proposed method is more accurate and effective than SVR and back propagation neural networks（BPNN）.

关键词： Wind Power Prediction Empirical Mode Decomposition Support Vector Regression Genetic Algorithm Fast Fourier Transform Wavelet Filter

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Speaker-independent Speech Emotion Recognition Based on Random Forest Feature Selection Algorithm 36

Speaker-independent Speech Emotion Recognition Based on Rand...

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第36届中国控制会议

作者： Wei-Hua Cao Jian-Ping Xu Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Feature selection is a crucial step in the development of a system for identifying emotions in *** to select high correlation features is an open *** paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion *** feature selection of speakerindependent speech based on Random Forest is proposed,which can remove the redundant features that have high correlations with each *** on the speech emotion recognition based on Support Vector Machines(SVM) is performed,where the speaker-independent features selected by the proposal and Spearman correlation analysis are used for emotion recognition,*** results show that the proposal achieves 78.6%recognition rate on average,which is 2.2%higher than using Spearman.

关键词： Emotion Recognition Speech Speaker-independent Feature Selection Random Forest

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LRDE:Long-Range Dependency and Salient Feature Enhancement for Co-SOD 41

LRDE:Long-Range Dependency and Salient Feature Enhancement f...

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第41届中国控制会议

作者： LongSheng Wei SiYuan Guo GuanYu Zong Jiu Huang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Different from other salient object detection(SOD) for the task of extracting salient obj ects in a image,collaborative saliency object detection(Co-SOD) targets a set of related image groups,and uses algorithms to find and locate the common collaborative salient objects in related image *** current SOD has achieved remarkable results,but most of the previous researches focus on how to obtain the consistency between images,while the contextual semantic information of images and the features of salient objects are less *** solve these problems,we propose a novel network to capture long-range dependencies on images and enhance(LRDE) the representation of salient ***,In LRDE,we capture the longrange dependencies by the Non-local module to obtain contextual semantic ***,in order to highlight the features of salient objects and enhance the representation of salient objects,we propose the Coordinate Attention module,which embeds the location-attention channel attention and encodes the feature maps as orientation-aware and position-aware attention maps,and It is applied complementary to the input feature map,thereby enhancing the representation of salient *** show that the method outperforms twelve improved methods on four publicly available datasets.

关键词： Co-SOD Long-Range Dependency Feature Enhancement Non-local Module Coordinate Attention Module

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Multi-layer Performance Assessment Method for Sintering Production Process control System 36

Multi-layer Performance Assessment Method for Sintering Prod...

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第36届中国控制会议

作者： Wei Jiao Xin Chen Min Wu Wei Hua Cao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

According to the hierarchical control system of sintering production process,a multi-layer performance assessment method is *** discuss the structure,function and technology used of multi-layer performance assessment strategy which is composed of sintering comprehensive coke ratio(CCR) assessment module,sintering ignition assessment module and fuzzy synthetic decision-making *** multi-layer performance assessment for sintering production process control system is realized based on sintering CCR prediction model,performance assessment method for sintering ignition control,and fuzzy synthetic evaluation *** proposed multi-layer performance assessment method is implemented on the simulation platform of the sintering production process in the laboratory,which effectively realized the performance assessment for sintering production process plant level control system,and then provides effective information for the staff to maintain the control system.

关键词： Hierarchical control system Performance assessment method Fuzzy synthetic evaluation Comprehensive coke ratio Sintering ignition control

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Performance Diagnosis of controller Based on Eigenvector Subspace K-mean Clustering 36

Performance Diagnosis of Controller Based on Eigenvector Sub...

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第36届中国控制会议

作者： Man Hao Wei-Hua Cao Min Wu Yan Yuan Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

To diagnose the specific reasons that lead to deterioration of controller performance and improve the diagnostic accuracy,a performance diagnosis method based on eigenvector subspace K-mean clustering is ***,the number of standard deterioration performance subspace with different degrees of deterioration information is increased on the basis of the eigenvector subspace distance diagnosis method,in which multiple distance values between eigenvector subspaces are ***,K-mean clustering is used to divide these distance values into two classes,and the clustering center with a maximum number of points is selected as the representative ***,current performance degradation factor is attributed to the category that represented by the nearest standard performance *** simulation,a double-tank model is established,and simulation result shows that average accuracy of controller performance diagnosis reaches 99.4%approximately.

关键词： controller performance performance diagnosis eigenvector subspace K-mean clustering

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Tea Bud Recognition Based on Machine Learning 41

Tea Bud Recognition Based on Machine Learning

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第41届中国控制会议

作者： Guangjun Wang Zhi Wang Yi Zhao Yangzheng Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Due to the low efficiency and high cost of manual tea picking,as well as the development and application of machine vision and image recognition technology,the mechanization and intelligence of tea picking will become a *** of all,this paper analyzed the advantages and disadvantages of several common target detection methods by using Matlab ***,considering cost,accuracy and real-time performance,the method of combining K-means clustering and image morphology processing is finally selected to extract tea ***,the method is reproduced on STM32 single chip ***,the effect was verified in the actual tea garden,which laid a foundation for the subsequent intelligent picking.

关键词： Machine learning K-means clustering STM32

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Improved stabilization conditions for T-S fuzzy systems with interval time-varying delay 36

Improved stabilization conditions for T-S fuzzy systems with...

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第36届中国控制会议

作者： LIAN Zhi HE Yong ZHANG Chuanke WU Min School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper is concerned with the stabilization problem for T-S fuzzy system with interval time-varying delay. By constructing a novel augmented LKF and using a developed reciprocally convex matrix inequality proposed in this paper to bound the derivative of the LKF, a delay-dependent stabilization condition based on parallel distributed compensation scheme is worked out for the closed-loop fuzzy system. Two numerical examples and an application to control of a truck-trailer are given to illustrate the effectiveness of our method.

关键词： Fuzzy systems Delay-dependent Stabilization Reciprocally convex matrix inequality

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An improved stability criterion for singular systems with time-varying delay via a relaxed integral inequality 36

An improved stability criterion for singular systems with ti...

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第36届中国控制会议

作者： ZHI Ya-Li HE Yong WU Min School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper concerns the stability problem of singular systems with time-varying delay. According to different delaypartition intervals, an augmented Lyapunov-Krasovskii functional with delay cross terms is constructed. Based on it, using the relaxed integral inequality technique is to obtain a less conservative stability criterion. As a result, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

关键词： Stability Singular systems with time-varying delay Lyapunov-Krasovskii functional Relaxed integral inequality

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A molecularly engineered large-area nanoporous atomically thin graphene membrane for ion separation

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Nature Communications 2025年第1期16卷 1-12页

作者： Dai, Ziwen Jin, Pengrui Yuan, Shushan Yang, Jiakuan Agrawal, Kumar Varoon Wang, Huanting Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin School of Environmental Science & Engineering Huazhong University of Science and Technology Hubei Wuhan 430074 China Department of Chemical Engineering KU Leuven Celestijnenlaan 200F Heverlee 3001 Belgium Laboratory of Advanced Separations (LAS) École Polytechnique Fédérale de Lausanne (EPFL) Sion CH-1950 Switzerland Department of Chemical and Biological Engineering Monash University Clayton VIC Australia

Atomically thin graphene membranes with sub-1-nm pores show promise for ion/molecular separation, osmotic energy generation, and energy storage. Narrowing the pore size distribution and controlling the surface charge are essential to achieve these applications. However, nanoporous graphene membranes fabricated via conventional methods possess a broad pore size distribution and inadequately regulated surface charge, limiting their applications. Herein, we present a molecular anchoring approach for scalable synthesis of nanoporous graphene membranes via a bottom-up technique, aiming to narrow the pore size distribution without reducing the pore density while simultaneously adjusting the charge properties of nanopores. By selecting suitable anchoring molecules, the custom-tailored pore size distribution and chemical functionality of nanoporous graphene membranes can be achieved. Leveraging the steric restriction effect, anchoring monomers selectively traverse larger nanopores to form ion-selective plugs, effectively repairing these nanopores. The centimeter-scale nanoporous graphene membrane with an ion-selective plug achieves high separation selectivity (K⁺/Na⁺=20, K⁺/Mg²⁺=330). Theoretical simulations indicate that a smaller pore size, narrow pore size distribution, and positive charge result in a larger energy barrier difference, leading to ultrahigh metal ion selectivity. Furthermore, in treating lithium battery leaching solutions, Li⁺/divalent ions selectivity exceeds 900. These findings provide a way for designing graphene-based membranes. © The Author(s) 2025.

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Tea Picking Path Planning Based on Ant Colony Algorithm 41

Tea Picking Path Planning Based on Ant Colony Algorithm

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第41届中国控制会议

作者： Guangjun Wang Yi Zhao Zhi Wang Yangzheng Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In order to improve the efficiency of tea picking,a scheme combining ant colony algorithm and tea picking technology is proposed to plan the picking *** this scheme,k-means clustering algorithm is used to divide the tea picking regions with irregular *** ant colony algorithm is used to carry out path planning for tea in different picking areas,and the best picking effect is selected according to the simulation *** solve the problem of long searching time of ant colony algorithm,the condition of iteration termination is changed to adaptive value,and the optimal route after the last iteration is recorded as the initial value of the next *** simulation results show that the best effect is to divide two picking *** improved ant colony algorithm reduces the operation time and the planned picking path is shorter,which can enhance the real-time tea picking and improve the efficiency of tea picking.

关键词： Tea plucking Path planning Ant colony algorithm K-means clustering

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