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Refrigerant capacity detection of dehumidifier based on time series and neural networks 1

13th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2018

作者： Peng, Gang Yang, Zuhuang Wang, Min School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry Wuhan China Shenzhen Institute Huazhong University of Science and Technology Shenzhen518060 China

ISBN: (数字)9789811328299

ISBN: (纸本)9789811328282

Refrigerant leakage is common in the use of dehumidifier, leading to decrease of dehumidification ability. To detect refrigerant capacity effectively and maintain it timely, a neural network with deep learning skills was proposed based on time series. As input of networks, the time series consists of the operating parameters of the dehumidifier at multiple time points. To determine the refrigerant capacity, the proposed method combines the outputs on the neural networks of all the time series examples in a single run of dehumidifier. As the result suggests, the proposed method is capable of detecting the refrigerant capacity with a low missing rate and high accuracy, which improves the maintenance mechanism of the dehumidifier and is of great significance to ensuring a comfortable air environment for user. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Time series

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Terrain Simplification Research in Augmented Scene Modeling

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Journal of China University of Geosciences 2001年第4期12卷 351-355页

作者： Ming Delie You Kefei Tian Jinwen Liu Jian State key laboratory for image processing and intelligent control, Institute for Pattern Recognition and Artificial Intelligence , Huazhong University of Science and Technology , Wuhan 430074 Wang Guangju State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

关键词： augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy.

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A uniform solution to common algorithmic problem by tissue p systems with cell division

A uniform solution to common algorithmic problem by tissue p...

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6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Niu, Yunyun Pan, Linqiang Pérez-Jiménez, Mario J. Key Laboratory on Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Research Group on Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla 41012 Spain

ISBN: (纸本)9780769545141

Common algorithmic problem is an optimization problem, which has the nice property that several other NPcomplete problems can be reduced to it in linear time. A tissue P system with cell division is a computing model which has two basic characters: intercellular communication and the ability of cell division. The ability of cell division allows us to obtain an exponential amount of cells in linear time and to design cellular solutions to computationally hard problems in polynomial time. We here present an effective solution to the common algorithmic decision problem using a family of recognizer tissue P systems with cell division. © 2011 IEEE.

关键词： Polynomial approximation

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A Local image Interpolation Method Based On Gradient Analysis

A Local Image Interpolation Method Based On Gradient Analysi...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Tian Yan Liu Bin Li Tao Department of electronic and information engineering Huazhong University of Science & Technology School of computer science and technology Huazhong University of Science & Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology

ISBN: (纸本)0780394224

image interpolation has been widely used and studied in the fields of image *** the different complexities along the different directions,a novel image interpolation method based on gradient analysis is presented in this ***,for each point that need to be interpolated,it's the gradient values along the horizontal and vertical directions are estimated ***,different interpolation methods are carried out along these two directions according to the gradient values,that is a higher order interpolation method is applied if the gradient value is greater than certain threshold;otherwise,a lower order interpolation method is *** method gives an attention to the precision and complexity of interpolation procedure. Experimental results show that the proposed method is feasible and promising.

关键词： Gradient image interpolation root mean square error

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Research of input decouple method of re-entry aircraft

Research of input decouple method of re-entry aircraft

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Ni, Shaobo Shan, Jiayuan Shang, Shuaifeng Aerospace College Beijing Institute of Technology Beijing 100081 China Beijing Institute of Aerospace Automatic Control Beijing 100854 China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780956715715

Re-entry aircraft depends on aerodynamic force during flight. Because of windward rudder and lee rudder, there certainly exists aerodynamic coupling among pitch channel, yaw channel and roll channel under the situation of large attack angle and slip angle, and behaves couplings of inputs and states. This paper proposed decouple control of inputs aiming at the coupling problem of inputs, and the MIMO problem is transformed to a SISO one. For the SISO problem, the coupling of states can be solved by control system design to guarantee system stable and robust. © 2012 Huazhong Univ of Sci & Tec.

关键词： Attitude control

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Adversarial Refinement Network for Human Motion Prediction 15th

Adversarial Refinement Network for Human Motion Prediction

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15th Asian Conference on Computer Vision, ACCV 2020

作者： Chao, Xianjin Bin, Yanrui Chu, Wenqing Cao, Xuan Ge, Yanhao Wang, Chengjie Li, Jilin Huang, Feiyue Leung, Howard City University of Hong Kong Hong Kong China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Tencent Youtu Lab Shanghai China

ISBN: (纸本)9783030695316

Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward deep networks, are able to predict rough motion trend, but motion details such as limb movement may be lost. To predict more accurate future human motion, we propose an Adversarial Refinement Network (ARNet) following a simple yet effective coarse-to-fine mechanism with novel adversarial error augmentation. Specifically, we take both the historical motion sequences and coarse prediction as input of our cascaded refinement network to predict refined human motion and strengthen the refinement network with adversarial error augmentation. During training, we deliberately introduce the error distribution by learning through the adversarial mechanism among different subjects. In testing, our cascaded refinement network alleviates the prediction error from the coarse predictor resulting in a finer prediction robustly. This adversarial error augmentation provides rich error cases as input to our refinement network, leading to better generalization performance on the testing dataset. We conduct extensive experiments on three standard benchmark datasets and show that our proposed ARNet outperforms other state-of-the-art methods, especially on challenging aperiodic actions in both short-term and long-term predictions. © 2021, Springer Nature Switzerland AG.

关键词： Errors

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The analysis and design of work safety and emergency management information system in large-scale hydroelectric project

The analysis and design of work safety and emergency managem...

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2009 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2009

作者： Zhou, Jian-Lan Sun, Zhi-Yu Liu, Xian-Rong Key Laboratory of Education Ministry for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei 430074 China Department of Work Safety China Three Gorges Project Corporation Yichang Hubei 443002 China

ISBN: (纸本)9781424424870

It is significant to research the work safe and emergency management information system (PSEMIS) in large-scale hydroelectric project. This paper analyses the reviews and China Three Gorges Project Corporation work safety and emergency management status and business needs, proposes the overall framework of the system design. The basis of the work safety management system and emergency management system is the safety risk control and hazards classification standards. The paper discusses the safety risk control and hazards classification standards;analyses the main function modules of the work safety and emergency management application software systems respectively;and discusses the hazards risk assessment and identification standards, business model design, systems integration, digital contingency plans and other key technical problems. © 2009 IEEE.

关键词： Hazards

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Kalman Filter Adaptive Speed Tracking control for High-speed Trains with Noise Interference 7

Kalman Filter Adaptive Speed Tracking Control for High-speed...

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7th International Conference on intelligent Robotics and control Engineering, IRCE 2024

作者： Zhang, Chunli Xie, Yuwei Yan, Lei Qian, Fucai Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing College of Automation and Information Engineering Xi'an China

ISBN: (纸本)9798350352399

In this paper, high-speed train is regarded as a single prime point, a new tracking control method combining adaptive control and Kalman filtering is proposed. This paper solves the noise interference problem in the tracking control process of high-speed train. The method first linearises the original system, then uses Kalman filtering to do model estimation, and the controller is designed for the predictive model through adaptive control. Finally, MATLAB is used to simulate and verify the effectiveness of this method. This proposed method successfully solves the problems of nonlinearity, noise interference and unknown parameters in system. The error caused by resistance in the high-speed train tracking control process can be dealt with effectively. © 2024 IEEE.

关键词： Kalman filters

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Gravel image Segmentation in Noisy Background Based on Partial Entropy Method

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中国地质大学学报(英文版) 2000年第1期11卷 92-94页

作者： Wang Guangjun Tian Jinwen Chen Zhenyu Liu Jian Wu Guoping State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuHan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.

关键词： partial entropy segmentation mathematical morphology gravel threshold filter

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Study on landslide deformation prediction based on recurrent neural network under the function of rainfall

Study on landslide deformation prediction based on recurrent...

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Chen, Huangqiong Zeng, Zhigang Tang, Huiming Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China Faculty of Engineering China University of Geosciences Wuhan Hubei 430074 China

ISBN: (纸本)9783642344770

Landslide deformation prediction has significant practical value that can provide guidance for preventing the disaster and guarantee the safety of people's life and property. In this paper, a method based on recurrent neural network (RNN) for landslide prediction is presented. The results show that the prediction accuracy of RNN model is much higher than the feedforward neural network model for Baishuihehe landslide. Therefore, the RNN model is an effective and feasible method to further improve accuracy for landslide displacement prediction. © 2012 Springer-Verlag.

关键词： Recurrent neural networks

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