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Image Semantic Segmentation Scheme based on XGBoost combination with Convolution Feature Extraction 41

Image Semantic Segmentation Scheme based on XGBoost combinat...

引用

第41届中国控制会议

作者： Zichen Dai Xuewen Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Aiming at the problem that the existing image semantic segmentation schemes based on convolutional neural network require a large number of training data sets and high training cost,this paper presents a novel scheme for image semantic segmentation based on extreme gradient boosting(XGBoost),a scalable tree boosting system and the combination of convolution feature extraction(CFE).The scheme consists of three ***,convolution operation is performed on a small amount of RGB pixel information of the image processed by Gaussian filtering to acquire more multi-dimensional image feature ***,some preprocessing techniques of image feature information,including feature normalization and image label pixel number uniformity are performed to match the ***,the preprocessed image feature information and corresponding labels are input into XGBoost to train and predict the data of the test *** simulation and practical tests,compared with other commonly used few data classification algorithms like k-Nearest-Neighbor(kNN) and Support-VectorMachine(SVM),this scheme can achieve high precision pixel-level image semantic segmentation under the condition of lower training cost.

关键词： Image Semantic Segmentation Convolutional Feature Extraction XGBoost Gaussian Filtering Low Training Cost

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Stability Analysis of Discrete-Time Delayed Neural Networks via A Cubic Function Negative-Determination Lemma 41

Stability Analysis of Discrete-Time Delayed Neural Networks ...

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第41届中国控制会议

作者： Wen-Hu Chen Fei Long Cui Zhu Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper is concerned with the stability analysis of discrete-time neural networks with a time-varying ***,an improved augmented Lyapunov-Krasovskii functional(LKF) is established by adding single/double-summation ***,by utilizing summation inequalities,the forward difference of the constructed functional is estimated as a cubic function with respect to the *** applying the cubic function negative-determination lemma,a less conservative stability criterion is obtained,whose advantages are demonstrated via a numerical example.

关键词： Discrete-time neural networks time-varying delay cubic function negative-determination lemma stability analysis

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An Analysis Method for Influence of BF Operating Parameters on GUR Based on Convergent Cross Mapping Algorithm 41

An Analysis Method for Influence of BF Operating Parameters ...

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第41届中国控制会议

作者： Chenglin Yang Jianqi An Weijun Li Wenkai Hu Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A blast furnace(BF),which includes a variety of complex physical changes and chemical reactions,has many operating parameters that affect its smelting ***,the relationship between operation parameters and state parameters is complex and the influence of time delay between operation parameters and state parameters is difficult to be ***,this paper proposes a convergent cross mapping algorithm(CCM) incorporating delay analysis to solve this ***,using the CCM algorithm to calculate the correlation coefficients between operation parameters and state parameters,and judge the causal relationship between each operating parameter and state parameter by the convergence of the CCM ***,determine the specific delay time and time delay interval of BF operating variables to state variables through fusion time delay *** that the selection of embedding dimension has an important influence on the result of causality *** paper uses the cross-validation method to determine the optimal embedding ***,by comparing the mechanism analysis and the experimental results,the effectiveness of this method in determining causality and delay time of BF variables is verified.

关键词： Blast Furnace Operation Parameters causal relationship Convergence Cross Mapping Time Delay

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Dynamic Sensing Modeling of Dielectric Elastomer Sensors Based on GRU Neural Network 6

Dynamic Sensing Modeling of Dielectric Elastomer Sensors Bas...

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6th International Conference on intelligent Robotics and control Engineering, IRCE 2023

作者： Zhang, Mingyi Huang, Peng Wang, Yawu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

ISBN: (纸本)9798350326338

Dielectric elastomer sensor (DES) is a flexible sensor that can perform free bending deformation, thus it has broad application prospects in the fields of medical electronics, wearable devices, soft robots, etc. Previous studies have mostly focused on exploring the static sensing characteristics of the DES. Considering that the DES may be used in dynamic conditions, it is very meaningful to study its dynamic sensing characteristics to broaden its application ranges. In this paper, a dynamic sensing model of the DES is established based on the gate recurrent unit (GRU) neural network. Firstly, the structure of the DES and the construction of the experimental system are introduced. In addition, the dynamic sensing characteristics of the DES are analyzed by conducting several sets of experiments, which shows that the DES has significant rate-dependent hysteresis nonlinearities, multivalued mapping and memory characteristics. After that, the dynamic sensing model of the DES is built based on the GRU neural network to describe the above dynamic sensing characteristics. Next, the dynamic displacement and force sensing models of the DES are trained according to the dynamic displacement-capacitance and dynamic force-capacitance experimental data, respectively. Finally, several experiments are performed to verify the effectiveness and generalization ability of the established dynamic sensing model. © 2023 IEEE.

关键词： Capacitance

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Research on Energy Storage control Strategy Considering Economy 41

Research on Energy Storage Control Strategy Considering Econ...

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第41届中国控制会议

作者： Zihan Zhang Zhijian Fang Jie Cai Wenhe Peng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Energy storage system is generally used to ensure the stability and reliability of *** the system generally contains multiple energy storage units,and due to the process,material and other aspects of the limitation,the initial state of charge(SOC) of each energy storage unit cannot be guaranteed to be completely equal,which leads to the shortening of the life of energy storage unit,and affect the economic benefits of energy storage system ***,this paper analyzes the influence conditions between energy storage units according to the calculated formula of energy storage unit *** value of charge between energy storage systems is analyzed through the active power output of the system,and then the difference is obtained by comparing the value of charge of each energy storage unit with the average value of charge of each *** the iterative algorithm is used to update the state of each node,and the balance factor is introduced to gradually reduce the difference on the basis of droop control to optimize and control the output of these energy storage nodes to achieve SOC *** the economic benefits such as maintenance cost of energy storage system are ***,a working model of microgrid is established and the feasibility and economy of this method are verified by simulation.

关键词： Economy Micro grid Energy storage system Droop control SOC balance

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Stability Analysis for Delayed Neural Networks via a Relaxed Negative-Determination Quadratic Function Method 41

Stability Analysis for Delayed Neural Networks via a Relaxed...

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第41届中国控制会议

作者： Yu-Long Fan Ke-You Xie Xing-Chen Shangguan Hongzhang Wang Chuan-Ke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents an improved stability condition for neural networks with a time-varying ***,an improved Lyapunov-Krasovskii functional(LKF) is constructed by introducing the delay-product term and the augmented ***,a less conservative delay-dependent stability criterion for neural networks with a time-varying delay is established by utilizing the generalized reciprocally convex combination and a relaxed quadratic function ***,a numerical example is used to illustrate the merit and effectiveness of the proposed stability criterion.

关键词： Neural Networks Time-varying Delay Stability Analysis Reciprocally Convex Matrix Inequality NegativeDetermination Method

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Efficient Facial Expression Recognition Network Based on Spot-Adaptive Knowledge Distillation 26

Efficient Facial Expression Recognition Network Based on Spo...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Wen, Xin Liu, Zhen-Tao Chen, Dan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9798331521950

Facial expression recognition plays a key role in promoting the development of comprehensive intelligence and building friendly human-computer interaction. Due to the interference of feature noise in expression data, the lightweight facial expression recognition model with fewer parameters is difficult to learn more expression features through simple training, which limits the improvement of its recognition performance. An efficient facial expression recognition network based on Spot-adaptive Knowledge Distillation is proposed in this paper. Inspired by VoVNetV2, the network designed in this paper is lightweightly improved using Depthwise Separable Convolution and the parameter-free SimAM attention mechanism, reducing the number of parameters to 0.21 M. To further improve the recognition accuracy of the model, Spot-adaptive Knowledge Distillation is employed to improve the characterization ability of the model. The recognition accuracies of the student network designed in this paper on the KDEF and RAF-DB datasets are 93.05% and 81.17% respectively after spot-adaptive distillation. © 2025 IEEE.

关键词： Facial Expression Recognition Knowledge Distillation Lightweight Neural Network

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An Improved Exponential Stability Criterion of Generalized Neural Networks With Intermittent Large-Delay Periods 41

An Improved Exponential Stability Criterion of Generalized N...

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第41届中国控制会议

作者： Jin-Meng Xu Yong He Wen-Hu Chen Zhe-Li Yuan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper focuses on the exponential stability analysis of generalized neural networks(GNNs) with time-varying delays,where the time delays include several intermittent large-delay periods(LDPs).First,the improved piecewise augmented Lyapunov-Krasovskii functional(LKF) candidate is constructed based on the delay-dependent state ***,some advanced inequalities are adopted to estimate the derivative of LKF *** with switching techniques,an exponential stability criterion with less conservativeness is *** last,a numerical example is used to verify the advantage of the proposed criterion.

关键词： Time-varying delay Switched delay system Large-delay period Exponential stability

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Model Predictive control for Interval Type-2 T-S Fuzzy systems Under New Dynamic Event-Triggered Mechanism 41

Model Predictive Control for Interval Type-2 T-S Fuzzy Syste...

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第41届中国控制会议

作者： Chaoling Zhang Fan Wei Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we focus on dynamic event-triggered model predictive control(MPC) problem for interval type-2 Takagi-Sugeno(IT2 T-S) fuzzy systems with hard constraints on the state.A dynamic event-triggered mechanism(DETM) with two adjusting variables is devised to reduce data transmission *** MPC problem is formulated as a "min-max" problem over the infinite *** purpose is to find a series of desired sub-controllers in terms of MPC such that the underlying IT2 T-S fuzzy system is asymptotically *** taking the T-S fuzzy nonlinearities and the DETM into consideration,we give the design method of the controller through an online auxiliary optimization problem with several constraint conditions.A simulation example is used to demonstrate the effectiveness and the validity of the proposed methods.

关键词： Dynamic event-triggered mechanism adjusting variables model predictive control interval type-2 T-S fuzzy systems

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Global Practical Sampled-data for a Class of Stochastic Nonlinear systems 41

Global Practical Sampled-data for a Class of Stochastic Nonl...

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第41届中国控制会议

作者： Qing Chang Shiqi Zheng Jiachun Sun Tao Song Liangguang Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we mainly study the global tracking problem for stochastic systems by the sampled data state feedback *** the condition of lower-triangular,the sampled data state feedback controller is constructed to make the states globally bounded,and the error between the system output and the reference signal is less than the specified allowable *** the same time stochastic phenomenon is considered in the nonlinear *** global tracking performance and stochastic stability are both achieved simultaneously.

关键词： Stochastic systems nonlinear systems state feedback sampled-data controllers

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