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2nd International Conference on Modelling and Simulation

作者： Zhu, Peiyi Xu, Benlian Xu, Baoguo Dept. of Automation Changshu Institute of Technology China School of Communication and Control Engineering Jiangnan University China

ISBN: (纸本)9781846260681

To solve the problem of power system reactive optimization efficiently, a new method, which combines particle swarm optimization algorithm with dynamic weight, was presented. The improved PSO algorithm, which is based on dynamic weight, is simple in application and quick in convergence. The weight is changed in every loop according to the swarm evolution degree and aggregation degree factor, which ensures population diversity and avoids premature convergence effectively. Then the algorithm is applied in reactive optimization of power system, compared with PSO, the optimization result s of IEEE-30-bus show that the algorithm has a good stable searching capacity and good parallel efficiency.

关键词： Reactive Flow Optimization Particle Swarm Optimization Evolution Degree Aggregation Degree Introduction

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Universal FRFT-based algorithm for parameter estimation of chirp signals

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Journal of Systems engineering and Electronics 2012年第4期23卷 495-501页

作者： Rong Chen Yiming Wang School of Electronics and Information Engineering Soochow UniversitySuzhou 215006P.R.China National Laboratory of Information Control Technology for Communication System Jiaxing 314001P.R.China

The realization of the parameter estimation of chirp signals using the fractional Fourier transform （FRFT） is based on the assumption that the sampling duration of practical observed signals would be equal to the time duration of chirp signals contained in the former. However, in many actual circumstances, this assumption seems unreasonable. On the basis of analyzing the practical signal form, this paper derives the estimation error of the existing parameter estimation method and then proposes a novel and universal parameter estimation algorithm. Furthermore, the proposed algorithm is developed which allows the estimation of the practical observed Gaussian windowed chirp signal. Simulation results show that the new algorithm works well.

关键词： fractional Fourier transform （FRFT） chirp signal,parameter estimation observation window.

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A Novel Multi-Points Laser Monitoring of Building Settlement and Its Risk Evaluation

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Wuhan University Journal of Natural Sciences 2019年第5期24卷 442-454页

作者： CHAI Caiping WU Zejian WANG Huifeng GUAN Limin HUANG He MU Kenan CUI Wenfen HAO Ting School of Highway & Railway Engineering Shaanxi College of Communication Technology Xi'an 714018 ShaanxiChina School of Electronic & Control Engineering Chang'an University Xi'an 710064 Shaanxi China

Aiming at the defects of routine settlement measurement methods, such as complicated procedures, time-consuming and labor-intensive, high cost and low measurement accuracy, based on the analysis of existing engineering measurement technical requirements and specifications, a multi-point high precision and high efficiency based on laser reference is proposed. The automatic building settlement real-time monitoring system program gives the principle and system model of single-point settlement observation. The model of multi-point scanning settlement monitoring system and the model of multi-point network settlement monitoring system are designed, and their advantages and disadvantages are analyzed. We focus on the networked multi-point settlement monitoring system for network cumulative error analysis, and propose related evaluation and correction methods. The hardware schematic and software block diagram of the laser reference measurement and measurement system of the single point settlement acquisition system are given. Finally, the risk of subsidence state is quantitatively evaluated based on multi-point settlement monitoring data. The measurement error of this method is less than 300 μm, which can realize the monitoring and evaluation of the overall settlement.

关键词： measurement technology laser reference settlement chain linear array Charge-Coupled Device(CCD)

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Fundamental frequency tracking of distorted power signal based on the improved EKF algorithm

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2015年第10期10卷 1-10页

作者： Xiaobing, Zhang Mengchen, Yang Yixin, Yan Guozhi, Fang College of Measure-control Technology and Communication Engineering Harbin University of Science and Technology Harbin China

To reduce the impacts of harmonics and noises on frequency measurements, a novel method of frequency tracking is presented based on improved EKF algorithm and wavelet transform. Firstly, the power signal was preprocessed to extract the fundamental wave by wavelet filtering. Then, an improved Extended Kalman Filter was introduced to achieve fast and accurate frequency tracking. By adding a robust factor and modifying the covariance matrix in real time, it enhanced the stability for detecting distorted signals. The proposed tracking algorithm can effectively solve the problems of traditional Extended Kalman Filter such as lack of adaptability, instability and divergence. And it improved the tracking speed and accuracy. Finally, Detailed simulations on several typical models of power signals have been carried out and the Simulation results shown that the new algorithm increases the speed, convergence and accuracy. It effectively suppresses the impacts of harmonics and noises on the frequency tracking results. © 2015 SERSC.

关键词： Wavelet transforms

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PDBSCAN: Parallel DBSCAN for Large-Scale Clustering Applications

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Journal of Donghua University(English Edition) 2012年第1期29卷 76-79页

作者：谢永红马延辉周芳刘颖安 School of Computer and Communication Engineering University of Science and Technology Beijing Key Laboratory for Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing

Density-based algorithm for discovering clusters in large spatial databases with noise(DBSCAN) is a classic kind of density-based spatial clustering algorithm and is widely applied in several aspects due to good performance in capturing arbitrary shapes and detecting outliers. However, in practice, datasets are always too massive to fit the serial DBSCAN. And a new parallel algorithm-Parallel DBSCAN(PDBSCAN) was proposed to solve the problem which DBSCAN faced. The proposed parallel algorithm bases on MapReduce mechanism. The usage of parallel mechanism in the algorithm focuses on region query and candidate queue processing which needed substantive computation resources. As a result, PDBSCAN is scalable for large-scale dataset clustering and is extremely suitable for applications in E-Commence, especially for recommendation.

关键词： parallel DBSCAN clustering MapReduce large-scale applications

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High-precision flow measurement for an ultrasonic transit time flowmeter

High-precision flow measurement for an ultrasonic transit ti...

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International Conference on Intelligent System Design and engineering Application (ISDEA)

作者： Hua, Meng Hui, Wang Mingwei, Li School of Control Science and Engineering Dalian University of Technology Dalian China School of Information and Communication Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9780769542126

In order to realize high-precision and real-time flow measurement, in this paper according to the measurement principle of ultrasonic transit time method, a low-power microprocessor MSP430 is used as the core of this system, and a high-precision measurement chip TDC-GP2 is specially adopted to collect the time difference signals in real time, hereby we design a new ultrasonic transit time flow-meter. On the basis of advanced hardware design above, to further improve the accuracy of flow measurement, a digital signal processing algorithm based on wavelet transform is adopted to de-noise the measured signals, which is rapidly realized in DSP chip. The experimental results show that the proposed method can effectively improve the measurement accuracy and real time performance, and meet the measurement requirements of flow-meter. © 2010 IEEE.

关键词： Flow measurement

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Two Algorithms Based on Iterative Optimization for UAV Path Planning

Two Algorithms Based on Iterative Optimization for UAV Path ...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Chen, Biao Li, Shengming Lv, Zongyang School of Control Science and Engineering Dalian University of Technology Dalian China School of Information and Communication Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350316308

In this paper, we propose two algorithms based on iterative optimization for UAV path planning. In the first one, a nonlinear programming (NLP) problem of unmanned aerial vehicle (UAV) path planning is transformed into a general quadratically constrained quadratic programming (QCQP) problem by a numerical optimization method and solved through iteration. This method can converge to the optimal solution without giving the initial value. It overcomes the problems that NLP solvers are dependent on the initial guess, slow to converge, and sometimes can't converge to a feasible solution. In the second one, we improve the optimized rapidly exploring random tree algorithm (RRT∗) and add UAV flight constraints to it. The improved RRT∗ algorithm reduces the length of the path and makes the path smoother. © 2023 IEEE.

关键词： Motion planning

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Optimized Methods for Online Monitoring of L-Glutamic Acid Crystallization

Optimized Methods for Online Monitoring of L-Glutamic Acid C...

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2021 International Conference on Signal Processing and Machine Learning, CONF-SPML 2021

作者： Yang, Timing Jiang, Chen Meng, Qi Dalian University of Technology School of Information and Communication Engineering Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China

ISBN: (纸本)9781665417341

In order to monitor the crystallization process of L-glutamic acid online, a real-time detection method based on non-invasive image analysis has been proposed to obtain in-situ images, and a deep-learning based network Mask R-CNN is applied to detect target crystals in images. Considering deep-learning network requires an enormous amount of dataset with labelled region of interest (RoI) samples, this paper proposes semi-automatic labelling methods to reduce human work when generating the dataset. By applying another Mask R-CNN for labelling the dataset, human work can be reduced from labelling the whole dataset to filtering the detection results of the labeller Mask R-CNN. The final detection results prove the feasibility of this method. The proposed method is also proved to be more feasible and reliable than transfer learning. © 2021 IEEE.

关键词： Deep learning

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A Survey on Negative Transfer

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 305-329页

作者： Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation expense,privacy concerns,***,the effectiveness of TL is not always *** transfer(NT),i.e.,leveraging source domain data/knowledge undesirably reduces learning performance in the target domain,and has been a long-standing and challenging problem in *** approaches have been proposed in the literature to address this ***,there does not exist a systematic *** paper fills this gap,by first introducing the definition of NT and its causes,and reviewing over fifty representative approaches for overcoming NT,which fall into three categories:domain similarity estimation,safe transfer,and NT *** areas,including computer vision,bioinformatics,natural language processing,recommender systems,and robotics,that use NT mitigation strategies to facilitate positive transfers,are also ***,we give guidelines on NT task construction and baseline algorithms,benchmark existing TL and NT mitigation approaches on three NT-specific datasets,and point out challenges and future research *** ensure reproducibility,our code is publicized at https://***/chamwen/NT-Benchmark.

关键词： Domain adaptation domain similarity negative transfer positive transfer transfer learning

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Prediction of Endpoint Phosphorus Content of Molten Steel in BOF Using Weighted K-Means and GMDH Neural Network

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Journal of Iron and Steel Research International 2012年第1期19卷 11-16页

作者： WANG Hong-bing XU An-jun AI Li-xiang TIAN Nai-yuan School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory of Advanced Control of Iron and Steel Process of Ministry of Education Beijing 100083China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing 100083China

The hybrid method composed of clustering and predicting stages is proposed to predict the endpoint phos- phorus content of molten steel in BOF （Basic Oxygen Furnace）. At the clustering stage, the weighted K-means is performed to generate some clusters with homogeneous data. The weights of factors influencing the target are calcu- lated using EWM （Entropy Weight Method）. At the predicting stage, one GMDH （Group Method of Data Handling） polynomial neural network is built for each cluster. And the predictive results from all the GMDH polynomial neural networks are integrated into a whole to be the result for the hybrid method. The hybrid method, GMDH polnomial neural network and BP neural network are employed for a comparison. The results show that the proposed hybrid method is effective in predicting the endpoint phosphorus content of molten steel in BOF. Furthermore, the hybrid method outperforms BP neural network and GMDH polynomial neural network.

关键词： basic oxygen furnace endpoint phosphorus content K-means neural network GMDH

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