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IEEE International Conference on Fuzzy Systems

作者： Hongmei Wang Tianhua Chen Hongtao Wang Xuqiang Shao Pan Su Science and Technology College North China Electric Power University China Department of Computer Science University of Huddersfield UK School of Control and Computer Engineering North China Electric Power University China

Anomaly detection aims to identify the abnormal instances, whose behavior deviates significantly from the others. Nowadays owing to the existence of diverse data generation sources, different attributes of the same instances may be located on distributed parties forming a multi-view dataset. Thus multiview anomaly detection has become a key task to discover outliers across various views. Traditionally, to perform multiview anomaly detection, one needs to centralize data instances from all views into a single machine. However, in many real-world scenarios, it is impractical to send data from diverse views to a master machine due to the privacy issues. Inspired by this, we propose a fuzzy clustering based distributed approach for multiview anomaly detection that simultaneously learns a membership degree matrix for each view and then detects anomalies for all parties. Specifically, we first introduce a combined fuzzy c-means clustering method for multi-view data and then design an anomaly measurement criterion to quantify the abnormal score from membership degree matrix. To solve the proposed model, a protocol is provided to unify all parties performing a well-designed optimization in an iterative way. Experiments on three datasets with different anomaly settings demonstrate the effectiveness of our approach.

关键词： Anomaly detection Distributed databases Optimization Protocols Data privacy Privacy Entropy

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Fault Classification Method of Information System Based on Cascaded Convolutional Neural Network Model 5

Fault Classification Method of Information System Based on C...

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5th IEEE International Conference on Information Systems and computer Aided Education, ICISCAE 2022

作者： Ou, Ruiting Chen, Shuo Qiao, Lin Liu, Ziang Cheng, Xu Qiao, Yongfeng State Grid Liaoning Information and Communication Company Shenyang China College of Computer Science and Engineering Northeastern University Shenyang China College of Economics and Management Shenyang Agricultural University Shenyang China Dandong Dongfang Measurement & Control Technology Co. Ltd Dandong China

ISBN: (数字)9781665481229

ISBN: (纸本)9781665481229

Artificial intelligence plays an important role in data anomaly detection, which can significantly improve the speed and accuracy of fault diagnosis and detection in power information system. With its powerful fitting ability, deep learning begins to emerge in various fields, especially in the field of da-ta anomaly detection, which can also use deep learning methods. Due to various types and similar features of power data sets, fault classification cannot be carried out accurately. At present, frequent detection of text information needs to be performed manually. To solve this problem, this paper proposes a fault classification method for information system based on cascaded convolutional neural network model. BERT deep learning network is used for model training, and a cascaded classification network is constructed. Multiple BERT models are called hierarchically to achieve the fault detection effect of hierarchical classification. The method presented in this paper improves the accuracy of fault prediction and classification, which also provides fast, accurate and reliable decision information basis for improving fault diagnosis. © 2022 IEEE.

关键词： Failure analysis

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Characteristics of transfers to and captures at Europa

Characteristics of transfers to and captures at Europa

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Spaceflight Mechanics 2006 - AAS/AIAA Space Flight Mechnaics Meeting

作者： Lam, Try Hirani, Anil N. Kangas, Julie A. Engineering Staff Guidance Navigation and Control Section Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena CA 91109 Department Computer Science University of Illinois at Urbana-Champaign 201 N. Goodwin Avenue Urbana IL 61801

ISBN: (纸本)0877035288

This paper explores the characteristics (i.e. stability and performance) of transfers to, and captures at Europa. We focus on optimal low-thrust transfers from Ganymede to potential science orbits at Europa and compare different capture types, transfer resonances, and thrust accelerations. The two types of capture methods we consider are capture in a distant retrograde orbit (DRO) and capture by targeting a state on a stable invariant manifold of a halo orbit. We show that each type has its advantages and disadvantages. The first part of DRO-type capture may be easier than a halo-type capture in some design schemes because DROs are generally extremely stable. However, halo-type captures using stable invariant manifolds typically result in fewer escapes even when full ephemeris is used. Moreover, changing the inclination to achieve a high inclination science orbit at Europa is much easier in a halo-type capture. We study these trade-offs in this paper.

关键词： Aerospace engineering

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An improved gene expression programming based on niche technology of outbreeding fusion

Informatica (Slovenia)

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Informatica (Slovenia) 2017年第1期41卷 25-30页

作者： Wang, Chao-Xue Zhang, Jing-Jing Wu, Shu-Ling Zhang, Fan Tromp, Jolanda G. School of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Department of Computer Science State University of New York Oswego United States

An improved Gene Expression Programming (GEP) based on niche technology of outbreeding fusion (OFN-GEP) is proposed to overcome the insufficiency of traditional GEP in this paper. The main improvements of OFN-GEP are as follows: (1) using the population initialization strategy of gene equilibrium to ensure that all genes are evenly distributed in the coding space as far as possible;(2) introducing the outbreeding fusion mechanism into the niche technology, to eliminate the kin individuals, fuse the distantly related individuals, and promote the gene exchange between the excellent individuals from niches. To validate the superiority of the OFN-GEP, several improved GEP proposed in the related literatures and OFN-GEP are compared about function finding problems. The experimental results show that OFN-GEP can effectively restrain the premature convergence phenomenon, and promises competitive performance not only in the convergence speed but also in the quality of solution.

关键词： Gene expression programming Niche technology Out breeding fusion

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AN ALGORITHM for AUTOMATED DETECTION of DELAYED BRAIN ISCHEMIA INDICATOR from VIDEO-EEG MONITORING DATA

AN ALGORITHM for AUTOMATED DETECTION of DELAYED BRAIN ISCHEM...

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2023 International Workshop on Photogrammetric and computer Vision Techniques for Environmental and infraStructure Monitoring, Biometrics and Biomedicine, PSBB 2023

作者： Murashov, D. Obukhov, Y. Kershner, I. Sinkin, M. Federal Research Center Computer Science and Control of RAS Moscow119333 Russia Kotel'Nikov Institute of Radio Engineering and Electronics of RAS Moscow125009 Russia N.V. Sklifosovsky Research Institute for Emergency Medicine Moscow Healthcare Department Moscow129090 Russia

In this work, we propose a new algorithm for detecting the indicator of delayed cerebral ischemia from video-EEG monitoring data. The proposed algorithm combines an algorithm for detecting the effect of interchannel time-frequency synchronization of wavelet spectrogram ridges of EEG signals and an algorithm for detecting motion artifacts in video recording frames. Using the EEG analysis algorithm, we identify an indicator that is used to predict the occurrence of ischemia. By analyzing the optical flow, we exclude time intervals in which erroneous fixation of ischemia indicators is possible. The developed algorithm was tested on the clinical data of video-EEG monitoring. The preliminary results obtained during testing confirm the fundamental possibility of detecting the ischemia indicators and the acceptable accuracy of detecting motion artifacts leading to an erroneous diagnosis. © Author(s) 2023. CC BY 4.0 License.

关键词： Optical flows

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Multi-Loss Function for Distance-to-collision Estimation

Multi-Loss Function for Distance-to-collision Estimation

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2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Zhang, Xiangzhu Zhang, Lijia Xu, DIng Pei, Hailong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Min. of Educ. Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong Guangzhou China Guangdong University of Technology School of Computer Science and Technology Guangzhou China

ISBN: (纸本)9781665402453

Estimation of the drone's distance-to-collision is the key to the indoor autonomous obstacle avoidance and navigation of monocular UAVs. At present, the distance-to-collision model mainly uses regression loss or ordinal regression for training Regression loss utilizes the continuity of distance, and ordinal regression loss utilizes the order of distance. To improve the prediction performance of the model, this paper proposes a multi-loss function trained deep learning model based on the linear combination of ordinal regression loss and regression loss. The regression loss can be obtained by adding a distance decoder after the ordinal regression estimation, without changing the original structure of the model. Finally, we test the model performance in public datasets and obtain good results. © 2021 IEEE.

关键词： Regression analysis

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Shunt Capacitor Bank Fault Detection and Localization Using Sub-Cycle Algorithm

Shunt Capacitor Bank Fault Detection and Localization Using ...

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IEEE Canada Electric Power Conference, EPEC

作者： Mohsen Tajdinian Behzad Behdani Ali Goodarzi Harold R. Chamorro Vijay K. Sood Department of Power and Control Engineering School of Electrical and Computer Engineering Shiraz University Shiraz Iran Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft the Netherlands Fars Electricity Distribution Company Fars Iran School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Computer and Software Engineering Faculty of Engineering and Applied Science Ontario Tech University Ontario Canada

ISBN: (纸本)9781665463195

Fast internal detection and location in Shunt Ca-pacitor Banks (SCBs) can lead to the prevention of damages to other SCBs' elements and consequently avoid undesirable performance and effects in power system operation. This paper targets the performance of phasor-based algorithms of failure detection and fault location of SCBs. Being dependent on the fundamental phasor components which usually are calculated based on the Discrete Fourier Transform (DFT), the failure detection and fault location algorithms suffer from almost one-cycle delay. This paper provides sub-cycle phasor estimation based on the least-square technique. The proposed algorithm is evaluated for different configurations of SCBs considering different fuse protection designs. The proposed method provides a criterion for relay decision-making in the case of multiple faulty phases condition. The proposed method is designed to monitor and detect consecutive failures based on the existing data of commercial relays. Performance evaluations are conducted under different circumstances namely voltage unbalance conditions and multiple internal fault locations.

关键词： Performance evaluation Fault detection Capacitors Discrete Fourier transforms Estimation Voltage Fault location

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A controller for electrification of vehicles by direct methanol fuel cell

A controller for electrification of vehicles by direct metha...

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2013 IEEE Energytech, Energytech 2013

作者： Zurawski, K. Sajadi, A. Institute of Control and Industrial Electronics Warsaw University of Technology Plac Politechniki 1 00-661 Warsaw Poland Electrical Engineering and Computer Science Department Case Western Reserve University Olin 613 10900 Euclid Avenue Cleveland OH 44106-7071 United States

ISBN: (纸本)9781467344449

This paper presents the design of a controller which electrifies vehicles by a direct methanol fuel cell. The project has been prepared based on a 1-4 scaled model of a car. As part of this project, an electronic motherboard including control algorithms for wireless system monitoring and car control has been developed. For wireless communication between the vehicle and the PC, a connection has been established based on ZigBee PRO standard. This connection is encrypted using an AES-128 algorithm. Finally, in order to verify the performance of the proposed controller, it has been installed on an actual car. © 2013 IEEE.

关键词： Zigbee

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PID2018 benchmark challenge: Model predictive control with conditional integral control using a general purpose optimal control problem solver - RIOTS. ?

arXiv

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arXiv 2018年

作者： Dehghan, Sina Zhao, Tiebiao Zhao, Yang Yuan, Jie Ates, Abdullah Chen, YangQuan University of California Merced MercedCA95340 United States School of Control Science and Engineering Shandong University Jinan Shandong250061 China School of Control Science and Engineering Southeast University Nanjing China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey

This paper presents a multi-variable Model Predictive control (MPC) based controller for the one-staged refrigeration cycle model described in the PID2018 Benchmark Challenge. This model represents a two-input, two-output system with strong nonlinearities and high coupling between its variables. A general purpose optimal control problem (OCP) solver Matlab toolbox called RIOTS is used as the OCP solver for the proposed MPC scheme which allows for straightforward implementation of the method and for solving a wide range of constrained linear and nonlinear optimal control problems. A conditional integral (CI) compensator is embedded in the controller to compensate for the small steady state errors. This method shows significant improvements in performance compared to both discrete decentralized control (C1) and multi-variable PID controller (C2) originally given in PID2018 Benchmark Challenge as a baseline. Our solution is introduced in detail in this paper and our final results using the overall relative index, J, are 0.2 over C1 and 0.3 over C2, respectively. In other words, we achieved 80% improvement over C1 and 70% improvement over C2. We expect to achieve further improvements when some optimized searching efforts are used for MPC and CI parameter tuning. Copyright © 2018, The Authors. All rights reserved.

关键词： Model predictive control

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An Expert System Shell for Analysis of Real Time Signals

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IFAC Proceedings Volumes 1989年第13期22卷 65-67页

作者： Tong Wei-Guang Zhao Lin-Liang Department of Automatic Control Shenyang Architectural and Civil Engineering Institute Shenyang 110015 PRC Department of Computer Science Northeast University of Technology Shenyang 110006 PRC

The interpreting and analysis of real time sampled signals is important for improvement of quality of products. This article developed an expert system shell ASESS for interpreting and analyzing the real time signals based on the analysis-synthesis (A-S) inference technology which frequently used by human expert in considering complex problems. The A-S technology is introduced. In order to meet the need of speed of real time control, in ASESS two measures are taken: 1. Knowledge classification and meta-rules are applied. 2. The system is developed with the combination of three languages: Assembler, Fortran and Prolog. Considering the vagueness in inference of human experts, the fuzzy inference technology are applied. The knowledge base of ASESS can be separated from inference engine and can be edited easily, so the system ASESS can be used effectively in different cases by adding appropriate knowledge in that field.

关键词： Expert systems analysis-synthesis meta-rules real time diagnosis

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