检索结果-内蒙古大学图书馆

Variable Selection Method Based on Partial Mutual Information and Its Application to NOx Emission Prediction

学校读者我要写书评

暂无评论

Variable Selection Method Based on Partial Mutual Informatio...

第三十九届中国控制会议

作者： QIN Tianmu ZHANG Jinzhe YOU Mo YANG Tingting North China Electric Power Research Institute Co. Ltd. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power University

Data-driven modeling methods are widely used in industrial processes as the foundation of control and *** selection of optimal variable set plays an important role in model *** order to enhance the model prediction accuracy,a partial mutual information(PMI) method was proposed to select the optimal variable *** were used to validate the effectiveness of PMI ***,PMI method was applied to select main influencing factors of NOx emission of coal-fired boiler and the selection results were used as inputs of three different data-driven *** comparison between the models with or without variable selection was *** results showed that the PMI method enhanced the model prediction accuracy and avoided the over-fitting problem.

关键词： NOx emission coal-fired boiler partial mutual information(PMI) data-driven modeling

Automated IoT based Smart Water Quality Assessment system

学校读者我要写书评

暂无评论

Automated IoT based Smart Water Quality Assessment System

International Conference on system Modeling & Advancement in Research Trends (SMART)

作者： Durgesh Pant Ashutosh Bhatt Muneer Khan O.P. Nautiyal Pankaj Adhikari USERC Dehradun Birla Institute of Applied Sciences Bhimtal Computer Control System Design Laboratory Russia

ISBN: (数字)9781728132457

ISBN: (纸本)9781728132464

The aim of this paper is to develop automated Internet of Things (IoT) based Water Quality monitoring system. The different sensors are used to monitor the different parameters of water. The whole system having Arduino to interface the sensors and GSM module for remotely monitoring the data. This complete system is solar powered. The device is useful for accessing the quality of water. It can monitor the different water bodies in real time. We are presenting a design and development of a cost effective system for real time water monitoring. Also the device can measure other physical and chemical properties of the water. The Apparatus consist of modules Turbidity Sensor, pH sensor, Temperature & TDS Sensor. All sensors are connected with Ardurino. Ardurino converts the signal form into system readable form and send it to GSM module. The GSM Module will send the sensed data to Smart devices/ cloud through IOT platform. The result can be accessed daily/weekly or monthly.

关键词： Internet of Things Total Dissolved Solid Power of Hydrogen (Ph) Global system for Mobile Liquid Crystal Display Internet of things TOTAL DISSOLVED SOLIDS Water Quality LIQUID CRYSTAL DISPLAY Sensors Global mobile communication-systems wireless phone water bodies

Low-latency federated learning over wireless channels with differential privacy

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Chen, Cailian Jin, Shi Han, Zhu Poor, H. Vincent School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Data61 CSIRO SydneyNSW2015 Australia The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations can vary widely due to imbalanced data distributions, potential demands on privacy protections, and quality of transmissions. In this paper, we aim to minimize FL training delay over wireless channels, constrained by overall training performance as well as each client's differential privacy (DP) requirement. We solve this problem in the framework of multi-agent multiarmed bandit (MAMAB) to deal with the situation where there are multiple clients confornting different unknown transmission environments, e.g., channel fading and interferences. Specifically, we first transform the long-term constraints on both training performance and each client's DP into a virtual queue based on the Lyapunov drift technique. Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach. More importantly, we propose two efficient solutions to this matching problem, i.e., modified Hungarian algorithm and greedy matching with a better alternative (GMBA), in which the first one can achieve the optimal solution with a high complexity while the second one approaches a better tradeoff by enabling a verified low-complexity with little performance loss. In addition, we develop an upper bound on the expected regret of this MAMAB based FL framework, which shows a linear growth over the logarithm of communication rounds, justifying its theoretical feasibility. Extensive experimental results are conducted to validate the effectiveness of our proposed algorithms, and the impacts of various parameters on the FL performance over wireless edge networks are also discussed. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

A Novel Person Re-ID Method based on Multi-Scale Feature Fusion

学校读者我要写书评

暂无评论

A Novel Person Re-ID Method based on Multi-Scale Feature Fus...

第三十九届中国控制会议

作者： Yuanyuan Li Xiaofei Wang Zhiqin Zhu Xinghua Huang Penghua Li Guanqiu Qi Yujun Rong Chongqing University of Posts and Telecommunications Key Laboratory of Complex System Safety and Control Ministry of EducationChongqing University Computer Information Systems Department Buffalo State College China Mobile (Hangzhou) Information Technology Co. Ltd.

Person re-identification（Re-ID） is a challenging but significant research topic. Previous methods based on global features are not pay much attention to the fine-grained feature information. While the methods based on local features strictly rely on the accurate pedestrian detection bounding-boxes to align the image pairs. In this paper, the Multi-Scale Feature Fusion Network is proposed which can extract global and local features simultaneously and to learn jointly. The network structure consists of two branches. One is a global branch for global feature learning, in this branch, we extract the whole body feature information of human body to express the pedestrian image as a whole. The other is a local branch for local feature learning. In the local branch, according to the characteristics of pedestrian’s human structure, we segment the image into 6 horizontal strips to bring the local feature representation of the pedestrian image. In addition, we use a novel integration of multiple loss functions to further improve the recognition accuracy of the network. Experiments on Market-1501 and DukeMTMC-reID datasets show that our proposed method can achieve state-of-the-art results.

关键词： Person re-identification Multi-scale feature fusion Feature learning Multiple loss functions

QoE-aware user association and resource allocation for mixed services in heterogeneous networks 2

学校读者我要写书评

暂无评论

QoE-aware user association and resource allocation for mixed...

2nd International Symposium on Application of Materials Science and Energy Materials, SAMSE 2018

作者： Li, Shuxian Tang, Liangrui Yan, Jiangyu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

In heterogeneous networks (HetNets), user association and resource allocation (UARA) is a great challenge for radio resource management (RRM). In this paper, a novel QoE-aware UARA scheme is proposed. The delay factor is introduced to QoE metric to weight delays' effect on service transmitting. Then the UARA scheme based on QoE is formulated as an optimization problem which is a mixed integer nonlinear programming (MINLP) problem. To solve the problem, we adopt the genetic algorithm (GA) and associate the user association and the resource with population and fitness respectively. Through the evolutions of genetic algorithm, the optimal UARA scheme can be worked out. The simulation results indicate that the proposed scheme can reduce packet loss rate, and improve the system load balancing performance. © Published under licence by IOP Publishing Ltd.

关键词： Resource allocation

Semidiscrete optical vortex droplets in quasi-phase-matched photonic crystals

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Xu, Xiaoxi Zhao, Feiyan Huang, Jiayao He, Hexiang Zhang, Li Chen, Zhaopin Nie, Zhongquan Malomed, Boris A. Li, Yongyao School of Physics and Optoelectronic Engineering Foshan University Foshan528000 China School of Electronic and Computer Engineering Peking University Shenzhen518055 China Physics Department Solid-State Institute Technion Haifa32000 Israel Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology Foshan University Foshan528000 China

A new scheme for producing semidiscrete self-trapped vortices ("swirling photon droplets") in photonic crystals with competing quadratic (χ(2)) and self-defocusing cubic (χ(3)) nonlinearities is proposed. The photonic crystal is designed with a striped structure, in the form of spatially periodic modulation of the χ(2) susceptibility, which is imposed by the quasi-phase-matching technique. Unlike previous realizations of semidiscrete optical modes in composite media, built as combinations of continuous and arrayed discrete waveguides, the semidiscrete vortex "droplets" are produced here in the fully continuous medium. This work reveals that the system supports two types of semidiscrete vortex droplets, viz., onsite- and intersite-centered ones, which feature, respectively, odd and even numbers of stripes, N. Stability areas for the states with different values of N are identified in the system's parameter space. Some stability areas overlap with each other, giving rise to the multistability of states with different N. The coexisting states are mutually degenerate, featuring equal values of the Hamiltonian and propagation constant. An experimental scheme to realize the droplets is outlined, suggesting new possibilities for the long-distance transmission of nontrivial vortex beams in nonlinear media. © 2023, CC BY.

关键词： Photonic crystals

Limit behaviors of extended Kalman filter as a parameter estimator for a sinusoidal signal

学校读者我要写书评

暂无评论

control Theory and Technology 2018年第3期16卷 203-211页

作者： Li XIE State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing 102206 China

In this note, the basic limit behaviors of the solution to Riccati equation in the extended Kalman filter as a parameter estimator for a sinusoidal signal are analytically investigated by using lira sup and lim inf in... 详细信息

关键词： Extended Kalman filter parameter estimator sinusoidal signal covariance matrix limit behavior

Spherical interpolated convolutional network with distance-feature density for 3D semantic segmentation of point clouds

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Wang, Guangming Yang, Yehui Zhang, Huixin Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Computer Science and Technology University of Cambridge United Kingdom

The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because of the unstructured property of point clouds. In this paper, a spherical interpolated convolution operator is proposed to replace the traditional grid-shaped 3D convolution operator. This newly proposed feature extraction operator improves the accuracy of the network and reduces the parameters of the network. In addition, this paper analyzes the defect of point cloud interpolation methods based on the distance as the interpolation weight and proposes the self-learned distance-feature density by combining the distance and the feature correlation. The proposed method makes the feature extraction of spherical interpolated convolution network more rational and effective. The effectiveness of the proposed network is demonstrated on the 3D semantic segmentation task of point clouds. Experiments show that the proposed method achieves good performance on the ScanNet dataset and Paris-Lille-3D dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

Cloud-assisted nonlinear model predictive control for finite-duration tasks

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Li, Nan Zhang, Kaixiang Li, Zhaojian Srivastava, Vaibhav Yin, Xiang The Department of Aerospace Engineering University of Michigan Ann ArborMI48109 United States The Department of Mechanical Engineering Michigan State University East LansingMI48824 United States The Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States The Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China

Cloud computing creates new possibilities for control applications by offering powerful computation and storage capabilities. In this paper, we propose a novel cloud-assisted model predictive control (MPC) framework in which we systematically fuse a cloud MPC that uses a high-fidelity nonlinear model but is subject to communication delays with a local MPC that exploits simplified dynamics (due to limited computation) but has timely feedback. Unlike traditional cloud-based control that treats the cloud as powerful, remote, and sole controller in a networked-system control setting, the proposed framework aims at seamlessly integrating the two controllers for enhanced performance. In particular, we formalize the fusion problem for finite-duration tasks by explicitly considering model mismatches and errors due to request-response communication delays. We analyze stability-like properties of the proposed cloud-assisted MPC framework and establish approaches to robustly handling constraints within this framework in spite of plant-model mismatch and disturbances. A fusion scheme is then developed to enhance control performance while satisfying stability-like conditions, the efficacy of which is demonstrated with multiple simulation examples, including an automotive control example to show its industrial application potentials. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control