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Chinese automation Congress (CAC)

作者： Jing Wang Xiao Wang Yuanyuan Guo Fei-Yue Wang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Institute of Smart Healthcare Systems Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In order to improve the accuracy of diagnosis and the effectiveness of treatment on chronic diseases, a parallel medical diagnostic and treatment system for chronic diseases is proposed in this paper. The system consists of the artificial system, computational experiments and parallel execution. Generally, the actual medical system includes real doctors, real patients, and the process of real doctors diagnosing and creating a treatment plan. Based on the components in actual medical system, the virtual doctors and virtual patients are created in artificial system. The computational experiments are to exhaustively explore and evaluate reasonable diagnoses and treatment options, so that the most accurate diagnosis and the best treatment plan are configured. The parallel execution between the artificial and the actual system includes the interaction between virtual doctors and real doctors as well as that between the virtual patients and actual patients. The parallel execution, on the doctors' end, is to ensure the precise diagnosis of diseases and the effectiveness of the treatment plan. On the other hand, the parallel execution, on the patients' end, is to provide patients with more personal guidance on following the treatment and to assist sending feedback to the system regarding the treatment effectiveness. As the chronic diseases generally require a long-term treatment, this parallel system can better accommodate the process by continuously monitoring the treatment and sending feedback to the model so as to actively optimize the treatment plan.

关键词： Medical diagnostic imaging Medical services Diseases Medical diagnosis Deep learning Neural networks Knowledge engineering

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A Computer-Aided Tuning Method for Microwave Filters by Combing T-S Fuzzy Neural Networks and Improved Space Mapping

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Computer Modeling in Engineering & Sciences 2018年第9期116卷 433-453页

作者： Shengbiao Wu Weihua Cao Can Liu Min Wu School of Automation China University of GeoscienceWuhanHubei430074China Nanchang Institute of Science and Technology.Nanchang Jiangxi330100China The Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubei430074China

A computer-aided tuning method that combines T-S fuzzy neural network(TS FNN)and offers improved space mapping(SM)is presented in this *** method consists of three main ***,the coupling matrix is effectively extracted under the influence of phase shift and cavity loss after the initial ***,the surrogate model is realized by using a T-S FNN based on subspace ***,the mapping relationship between the actual and the surrogate models is established by the improved space mapping algorithm,and the optimal position of the tuning screws are found by updating the input and output parameters of the surrogate ***,the effectiveness of different methods is verified by an experiment with a nine order cross coupled *** results show that,compared to a back propagation neural network method based on electromagnetic simulation and an SM method based on a least squares support vector machine,the proposed method has obvious advantages in terms of tuning accuracy and tuning time.

关键词： Computer-aided tuning T-S FNN S-parameters coupling matrix

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Pro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails

arXiv

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arXiv 2021年

作者： Zhang, Yang Yu, Xin Lu, Xiaobo Liu, Ping The Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China The Australian Institute of Artificial Intelligence University of Technology Sydney UltimoNSW2007 Australia The School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Singapore138634 Singapore

In this paper, we study the task of hallucinating an authentic high-resolution (HR) face from an occluded thumbnail. We propose a multi-stage Progressive Upsampling and Inpainting Generative Adversarial Network, dubbed Pro-UIGAN, which exploits facial geometry priors to replenish and upsample (8×) the occluded and tiny faces (16×16 pixels). Pro-UIGAN iteratively (1) estimates facial geometry priors for low-resolution (LR) faces and (2) acquires non-occluded HR face images under the guidance of the estimated priors. Our multi-stage hallucination network upsamples and inpaints occluded LR faces via a coarse-to-fine fashion, significantly reducing undesirable artifacts and blurriness. Specifically, we design a novel cross-modal attention module for facial priors estimation, in which an input face and its landmark features are formulated as queries and keys, respectively. Such a design encourages joint feature learning across the input facial and landmark features, and deep feature correspondences will be discovered by attention. Thus, facial appearance features and facial geometry priors are learned in a mutually beneficial manner. Extensive experiments show that our Pro-UIGAN attains visually pleasing completed HR faces, thus facilitating downstream tasks, i.e., face alignment, face parsing, face recognition as well as expression classification. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A novel online learning RECOC-KFDA method for lithologic identification in drilling process*

A novel online learning RECOC-KFDA method for lithologic ide...

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Asian control Conference

作者： Xi Chen Weihua Cao Chao Gan Min Wu School of Automation China University of Geosciences and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781728102634

Aiming to achieve a safe and efficient drilling, this paper is concerned with identification of formation lithology, which provides critical information for drilling control. Notice that it is hard to make accurate geological prediction using conventional identification approaches, due to the data characteristics of imbalanced, multi-classification and low value density, a novel reduction error correcting output code kernel fisher discriminant analysis algorithm(RECOC-KFDA) method is developed in an online manner. It consider design optimal error correcting output code(ECOC) matrix based on a reduction algorithm, and it proposed an online method to reduce the computation complexity required for updating the kernel fisher discriminant analysis(KFDA) classifiers rather than recalibrating them. Proposed method has been applied to lithologic identification in drilling site. Simulations and comparisons demonstrate that our method is superior to the existing ones for both offline training and online prediction model.

关键词： Encoding Computational modeling Kernel Geology Drilling machines Data models Diversity reception

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A joint mid-course and terminal course cooperative guidance law for multi-missile salvo attack

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Chinese Journal of Aeronautics 2018年第6期31卷 1311-1326页

作者： Jie ZENG Lihua DOU Bin XIN School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Intelligent Control and Decision of-Complex Systems Beijing 100081 China

Salvo attacking a surface target by multiple missiles is an effective tactic to enhance the lethality and penetrate the defense system. However, existing cooperative guidance laws in the midcourse or terminal course are not suitable for long-and medium-range missiles or stand-off attacking. Because the initial conditions of cooperative terminal guidance that are generally generated from the mid-course flight may not lead to a successful cooperative terminal guidance without proper mid-course flight adjustment. Meanwhile, cooperative guidance in the mid-course cannot solely guarantee the accuracy of a simultaneous arrival of multiple missiles. Therefore, a joint mid-course and terminal course cooperative guidance law is developed. By building a distinct leader-follower framework, this paper proposes an efficient coordinated Dubins path planning method to synchronize the arrival time of all engaged missiles in the mid-course flight. The planned flight can generate proper initial conditions for cooperative terminal guidance, and also benefit an earliest simultaneous arrival. In the terminal course, an existing cooperative proportional navigation guidance law guides all the engaged missiles to arrive at a target accurately and *** integrated guidance law for an intuitive application is summarized. Simulations demonstrate that the proposed method can generate fast and accurate salvo attack.

关键词： Cooperative systems Dubins path Mid-course flight Missile guidance Salvo attack

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Signal discrimination with wavelet algorithm and Pearson correlation-based algorithm in φ-OTDR systems

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Journal of Physics: Conference Series 2021年第1期1738卷

作者： Dai Li Mo Zhi Hua Yu Yun Fei Cai Rui Liu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan 430074 China

This paper presents a novel method of distinguishing signal, the way expected to reduce the nuisance alarm rate since the high nuisance alarm rate will restrict the capability of phase-sensitive optical time-domain reflection technology. The proposed method includes two parts: wavelet positioning mutation to obtain the perturbation area and Pearson correlation algorithm to directly convert the intensity of the perturbation into a useful amplitude. This technique avoids the use of irrelevant data in these differential signals and provides a simple and feasible new approach for distinguishing signal and optimizing the positioning speed of φ-OTDR systems.

关键词：

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Urban Trip Generation Forecasting Based on Gradient Boosting Algorithm

Urban Trip Generation Forecasting Based on Gradient Boosting...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhishuai Li Gang Xiong Yu Zhang Meng Zheng Xisong Dong Yisheng Lv State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Beijing China

The four-step transportation model plays an important role in urban planning. The quality of the first phase, i.e. trip generation, determines the performance of the global course. The majority of trip generation forecasting models highly rely on mathematical derivation and have many predictor variables during the prediction, which leads to low accuracy of results and requires laboriously hand-crafted design of input vectors. This paper is the first to introduce the gradient boosting decision tree (GBDT) algorithm for trip generation prediction, and harmonizes such a powerful machine learning method with traditional urban planning requirements to achieve better prediction performance. Unlike the commonly used linear regression method, GBDT can automatically perform feature selection and model the non-linear relationships between input and output variables. Experimental results on real-world residential travel census in Beijing prove that the GBDT model significantly outperforms the baseline and can forecast the trip generation more accurately.

关键词： Machine learning algorithms Urban planning Transportation Predictive models Prediction algorithms Feature extraction Boosting

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CNN-based Broad Learning with Efficient Incremental Reconstruction Model for Facial Emotion Recognition ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10236-10241页

作者： Luefeng Chen Min Li Xuzhi Lai Kaoru Hirota Witold Pedrycz School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Tokyo Institute of Technology Yokohama 226-8502 Japan Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6R 2G7 Canada

Convolutional neural network-based broad learning with efficient incremental reconstruction model (CNNBL) is proposed to recognize emotions in human-robot interaction. It aims to extract deep and abstract features from facial emotional images, and reduce the influence of the complex structure and slow network updates on facial emotion recognition in deep learning. Feature extraction is carried out by convolution and maximum pooling, and then the ridge regression algorithm is used for emotion recognition. When the network needs to expand, the network is dynamically updated by incremental learning algorithm. We verified the experimental performance through k -fold cross validation. According to the recognition results, the accuracy on JAFFE database of our proposal is greater than that of the state of the art, such as the Local Binary Patterns with Softmax and Deep Attentive Multi-path convolutional neural network.

关键词： Convolution Neural Networks Broad Learning Emotion Recognition Human-Robot Interaction

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Parallel Building Process Management System

Parallel Building Process Management System

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Chinese automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： automation Digital twin Buildings User interfaces Software Engines Business

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A Modular Magneto-Inductive Sensor for Low Vector Magnetic Field Measurements

arXiv

引用

arXiv 2020年

作者： Liu, Huan Wang, Xiaobin Zhao, Changfeng Wang, Zehua Jian, Ge Dong, Haobin Liu, Zheng School of Automation China University of Geosciences Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Wuhan430074 China School of Engineering University of British Columbia Okanagan Campus KelownaBCV1V 1V7 Canada

The low magnetic field measurement has been utilized since ancient times in order to find economic resources, to detect magnetic anomalies, etc. In this case, the vector magnetic survey can simultaneously obtain the modulus and direction information of the magnetic field, which can contribute to obtaining more precise information and characteristics of magnetic field resources. This paper is concerned with the potential to exploit the signals of vector magnetic field measurement with a magneto-inductive (MI) sensor. To evaluate the capability of the MI sensor, a test platform is set up and its performance including the noise floor, the resolution, the sensitivity, etc., are comprehensively characterized. Further, a comparative geomagnetic observation and magnetic anomaly detection among the proposed MI sensor, a high-precision Overhauser sensor, and a commonly used and accepted commercial MI sensor are conducted. The experimental results identify the capability of the proposed MI sensor in weak magnetic detection. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic fields

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