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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是331-340 订阅

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Application of Gradient Tree in Credit Evaluation of Chinese Peasant Households

Application of Gradient Tree in Credit Evaluation of Chinese...

引用

data driven control and learning systems (ddcls)

作者： Wen Xiao Zhihui Yang School of Statistics and Applied Mathematics Anhui University of Finance and Economics Bengbu

the traditional peasant household credit evaluation is not only subjective, but also complex, time-consuming and inefficient with the help of experts9; experience. In this paper, the research data of China family s... 详细信息

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

the traditional peasant household credit evaluation is not only subjective, but also complex, time-consuming and inefficient with the help of experts' experience. In this paper, the research data of China family survey and research center are used to establish an evaluation model of China's peasant household credit with the help of the gradient tree model in the machine learning algorithm, and the AUC and F1 score are used to verify the evaluation results of the model. the empirical results show that the gradient tree model has a good prediction ability in peasant household credit evaluation, and it can be used as a new evaluation method in peasant household credit evaluation in China.

关键词： Predictive models Regression tree analysis Indexes Production Economics Finance data models

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Feedback control Based Optimization of Batch Processes in the Reduced Space

Feedback Control Based Optimization of Batch Processes in th...

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data driven control and learning systems (ddcls)

作者： Bobo Kong Lingjian Ye Feifan Shen Ningbo Institute of Technology Ningbo China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

the feedback control based optimization of batch processes is to enforce the necessary conditions of optimality in a feedback control manner, instead of explicit numerical optimizations. the control-based optimization does not involve parameter estimation and expensive computations for optimization, while the scheme is able to cope with uncertainties and restore optimality. However, the dimension of necessary conditions of optimality is generally large owing to the input parameterization, which significantly complicates the control task. this paper proposes an approach that can simplify the optimization problem by identifying the principal subspace of plant inputs, which are laid in a small dimension while still retaining most of the optimization performance. A batch reactor is studied to show the effectiveness of the new approach.

关键词： Optimization Uncertainty Feedback control Batch production systems Sensitivity control systems Shape

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ADHDP-Based Housing Energy Management For Two Housing Units With Mobile Storage

ADHDP-Based Housing Energy Management For Two Housing Units ...

引用

data driven control and learning systems (ddcls)

作者： Jiguang Xue Chunsheng Yan Lu Liu Jiahan Wang Xuliang Zhao Xin Wang Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd Shenyang China LiaoNing Electric Power Development Stock Co. LTD Shenyang China Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this paper, a new optimal learning control scheme for discrete-time nonlinear systems using iterative adaptive dynamic programming (ADP) approach is developed to obtain the optimal control law for two-house energy systems. First, the operation modes of the battery are analyzed, and the problem statement is carried out. Next, according to the data of the users, action dependent heuristic dynamic programming (ADHDP) is developed to obtain the optimal control law. Numerical results are given to illustrate the performance of the present method.

关键词： Optimal control Heuristic algorithms Energy management Dynamic programming Batteries Dynamic scheduling Vehicle dynamics

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Compound Disturbance Rejection control for Nanopositioning Using a Phase-Locking Loop Observer

Compound Disturbance Rejection Control for Nanopositioning U...

引用

data driven control and learning systems (ddcls)

作者： Wei Wei Pengfei Xia Zaiwen Liu Min Zuo Beijing Technology and Business University Beijing P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In nano-positioning, accuracy and speed are important issues to guarantee the system performance. Integral resonant control (IRC) is able to improve the bandwidth, and phase-locking loop observer (PLLO) based active disturbance rejection control (ADRC) is capable of achieving better closed-loop accuracy. By combining the advantages of PLLO based ADRC and IRC, a compound control technique is proposed. the compound control can deal with hysteresis and vibration, which are main factors affecting the accuracy and speed of a nano-positioning stage driven by a piezoelectric actuator. An identified model of a nano-positioning stage is utilized, and simulations have been performed. Presented numerical results confirm the proposed compound control technology.

关键词： Hysteresis Observers Compounds Nanopositioning Resonant frequency Mathematical model Damping

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Iterative learning control for Multiple Time-Delays Discrete systems in Finite Frequency Domain

Iterative Learning Control for Multiple Time-Delays Discrete...

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data driven control and learning systems (ddcls)

作者： Xiaohui Li Jianqiang Shen Hongfeng Tao Shoulin Hao Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan University Wuxi P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper developes iterative learning control scheme and the stability conditions for multiple time-delays discrete system. By formulating the problem over repetitive process form using 2D theory, sufficient stability conditions for multiple time-delays discrete system are developed along the trial, which guarantees the trial-to-trial error monotonic convergence. Moreover, the generalized Kalman-Yakubovich-Popov (KYP) lemma allows the iterative learning control scheme to develope stability conditions with LMI constraints and analyze in the finite frequency domain. A numerical simulation for multiple time-delays discrete system is given to verify the proposed method.

关键词： Stability analysis Numerical stability Convergence Delays Time-frequency analysis Process control Iterative learning control

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data Analysis and Practical Strategies on Opioid Crisis

Data Analysis and Practical Strategies on Opioid Crisis

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data driven control and learning systems (ddcls)

作者： Donghao Yang Zhihui Yang School of Mathematical Science Huaibei normal university Huaibei China School of Statistics and Applied Mathematics Anhui University of Finance and Economics Bengbu China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In view of the time-dependent spread and characteristics of synthetic opioids and heroin reported between five states and their counties in the US, aiming at the correlation analysis between opioid-like use and the social and economic data of the US census, the optimal C5.0 algorithm and data flow network model are used to model the decision tree, and the quantitative results of the related factors of opioid-like use are obtained. We try to simplify the model, making the whole process clear, easy to understand. the practices described herein provide one set of practical strategies and tools for potential use.

关键词： Drugs Correlation data models Analytical models Pain Market research Surgery

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A Pattern-moving-Based data-driven control Method for a Kind of Industrial Production Processes

A Pattern-moving-Based Data-driven Control Method for a Kind...

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data driven control and learning systems (ddcls)

作者： Xiangquan Li Zhengguang Xu Mushu Wang Jiarui Cui Xu Yang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Ministry of Education Beijing China School of Information Science and Electrical Engineering Shandong Jiaotong University Jinan China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Due to the existence of a kind of industrial production process which is too complex to determine the model structure and identify the system parameters, a data-driven control method is proposed based on pattern moving. First of all, the way of system dynamics description based on pattern moving is introduced. then, according to the mentioned way a pattern-moving-based model free adaptive control (PMFAC) algorithm is put forward, and pseudo orders of the PMFAC algorithm are identified by using the conditional entropy of output classes. At last, simulation results demonstrate the feasibility and effectiveness of proposed data-driven control method.

关键词： Mathematical model Aerospace electronics Process control Entropy System dynamics Numerical models Predictive models

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Active Disturbance Rejection control for Discrete systems

Active Disturbance Rejection Control for Discrete Systems

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data driven control and learning systems (ddcls)

作者： Haiyan Wang Tianhong Pan Zhiqiang Gao Huiyu Jin Anhui University Hefei China Jiangsu University Zhenjiang China Cleveland State University Cleveland Ohio USA Xiamen University Xiamen City China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

A form of active disturbance rejection control (ADRC) is proposed for a kind of discrete systems in this paper. the state space form of the system is firstly formulated. then the extended state observers (ESO) with and without model information are presented to estimate states and total disturbance. the control law is formulated to reject disturbance and to track a given trajectory. As a case study, the semiconductor manufacturing process is used to validate the proposed solution. Comparing with the exponentially weighted moving average controller, simulations indicate that the proposed discrete ADRC is effective in cancelling disturbance and in tracking the desired target.

关键词： Manufacturing processes Observers Tools Semiconductor device modeling Robust control Target tracking White noise

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Co-occurrence Mining of "data driven control", "model free adaptive control" and "iterative learning control" in Chinese Dissertation data

Co-occurrence Mining of "data driven control", "model free a...

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data driven control and learning systems (ddcls)

作者： Xiangpeng Liu Yang Ai Lantian Guo Ronghu Chi School of Mathematics and Physics Qingdao University of Science and Technology Qingdao China School of Automation and Electronics Engineering Qingdao University of Science and Technology Qingdao China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper focuses on the master and doctoral dissertations on "data-driven control", "model-free adaptive control" and "iterative learning control" collected by Chinese National Knowledge Infrastructure (CNKI) database before October 31, 2019. Exploiting big data technology, three topics mentioned above are studied in the form of mapping knowledge graph by Python, ROSTCM and Ucinet social network analysis software. Our research mainly explores and analyzes the temporal evolution as well as development status of the subject words, the cultivation organizations, the fund support, the co-occurrence of key words, the co-occurrence of dissertations topics and the characteristics of supervisor -student relationship, etc., which can provide references for relevant research fields.

关键词： Medical services data mining Organizations Market research Software Adaptation models data models

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Bagging-ELM Model for Heating Furnace thermal Efficiency Prediction

Bagging-ELM Model for Heating Furnace Thermal Efficiency Pre...

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data driven control and learning systems (ddcls)

作者： Kai Shang Xianglong Zeng Xiaorui Dong Shengli College China University of Petroleum Shandong China China Huanqiu Contracting & Engineering (Beijing) Co. Ltd Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

thermal efficiency is a very important index for heating furnace in chemical industry. In order to predict the complicated variables, the Bagging-ELM network based on ensemble learning and Extreme learning Machine is adopted. the proposed model is applied to predicting the net hourly electrical energy output in Combined Cycle Power Plant data set and the thermal efficiency of the heating furnace. there is a comparison between the results generated by Bagging-ELM model and those generated by BP model, RBF model, ELM model. Compared with other models, the Bagging-ELM can obtain higher accuracy and stability.

关键词： Furnaces data models Predictive models Training Neurons Mathematical model Prediction algorithms

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