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检索条件"主题词=Filtering algorithms"

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Efficient counting of balanced (2, k)-bicliques in Signed Bipartite Graphs

Efficient counting of balanced (2, k)-bicliques in Signed Bi...

引用

IEEE International Conference on Big Data

作者： Mekala Kiran Apurba Das Suman Banerjee Birla Institute of Technology & Science Hyderabad India Indian Institute of Technology Jammu Jammu & Kashmir India

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Analysis of large-scale networks for different structural patterns (also called motifs) remains an active area of research in the domain of graph data management and mining. In the past three decades, research has led to a large volume of literature in this area. However, the literature in the context of a signed bipartite graph is limited. In this paper, we study the problem of counting the balanced motifs in a signed bipartite graph. Specifically, We design an efficient algorithm BB2K for counting balanced (2, k)-bicliques. Previous studies for balanced bicliques in a signed bipartite graph focus on a set enumeration-based approach. We observe that the set enumeration-based approaches are expensive as they need to discard a large number of structures, which are not balanced. We take a different approach where we systematically group the symmetric and asymmetric wedges and count the balanced bicliques by counting on those wedges in such a way that we eliminate the generation of unbalanced structures completely. We conducted experiments with nine real-life datasets, and the experimental results demonstrate that our algorithm BB2K is more than 100× faster than the baseline SBCList++ - an adaptation of the state-of-the-art algorithm BCList++ combined with the filtering technique to filter out unbalanced bicliques. We have also shown the scalability of the proposed algorithm by using datasets of different sizes in our experiments.

关键词： filtering Scalability filtering algorithms Big Data Bipartite graph Data mining

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Research on Global Path Planning Technology for Field Maneuver of Armored Platforms

Research on Global Path Planning Technology for Field Maneuv...

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Artificial Intelligence, Internet of Things and Cloud Computing Technology (AIoTC), International Conference on

作者： Yan Cui Kaifeng Zheng Pu Li Haijiao Wei China North Artifical Intelligence&Innovation Research Institute Beijing China China North Vehicle Research Institute Beijing China

ISBN: (数字)9798331530280

ISBN: (纸本)9798331530297

Aiming at practical field operations for armored platforms and addressing the poor practicality of the results of traditional elevation data-based field maneuver path planning for armored vehicles due to the inadequate precision of elevation data, this paper explores the method of constructing an environmental grid map model based on vector layers of field road surfaces. By performing three-level buffer calculations on the road layers, different passability probabilities are assigned to the outer, middle, and inner layers, effectively avoiding the problem of $A^{*}$ path planning results sticking too closely to obstacle edges. Additionally, for the A* path search strategy, a reverse search approach with the technical implementation method of traversing the open list before the close list is adopted, improving efficiency by approximately $2 / 3$ compared to the traditional A* algorithm implementation. Furthermore, a method of updating the end node position by expanding layer by layer from the end node is employed to solve the problem of path planning failure when the end node is located on an impassable grid. Finally, the weighted recursive average filtering algorithm is applied to smooth the planning results, meeting display requirements and the needs of unmanned vehicles.

关键词： Solid modeling Roads Probability filtering algorithms Search problems Path planning Data models Vectors Planning Autonomous vehicles

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Optimal reactive power control for 3-phase EMT SVC grid-connected converter

Optimal reactive power control for 3-phase EMT SVC grid-conn...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Mohamed Kouki Baptiste Trajin Paul-Etienne Vidal Production Engineering Laboratory University of Technology Tarbes Occitanie Pyrenees (UTTOP) Tarbes France

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

Nowadays, the integration of power electronics into power systems has increased significantly. As a result, power grids were subject to numerous transformations. Hence, operations, power factor corrections, and voltage control of the grid-connected converters have become challenging tasks subject to enhancing the stability, reliability, and performance of the power grid. For this, we propose in this paper an advanced state-feedback control using the linear quadratic regulator (LQR) optimized by the metaheuristic method for a 2-level 3-phase voltage source converter (VSC) connected to the utility grid through an output L-type or LCL-type filter. The proposed methodology avoids the empirical trial-and-error technique for adjusting the weighting values of matrices Q and R respecting multi-objectives: (i) minimize control loop errors, (ii) minimize the overshoot, and (iii) respect suitable time constant. Thus, the optimal weighting matrices are provided using the multi-objectives Tunicate Swarm Algorithm-TSA. The effectiveness of the proposed methodology is tested on Electromagnetic Transients (EMT) VSC grid-connected systems and compared to standard vector control and advanced control (H ∞ ). The proposed methodology permits important performance regulation of reactive power for the feasible VSC operation range and under perturbation conditions (short circuits,…).

关键词： Europe Static VAr compensators Power system stability filtering algorithms Linear programming Smart grids Voltage control Matrix converters Standards Voltage-source converters

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A Combined Step-size Filtered-x Affine Projection Champernowne Algorithm for Active Noise Control

A Combined Step-size Filtered-x Affine Projection Champernow...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Seung Hyun Ryu Jeongmin Park PooGyeon Park Department of Electrical Engineering POSTECH Pohang Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The study proposes the combined step-size affine projection Champernowne adaptive filter (CSS-APCMAF), addressing the back-and-forth relationship between convergence rate and steady-state misalignment in fixed step-size adaptive filtering algorithms. Additionally, the study introduces a new approach to active noise control using the combined step-size filtered-x affine projection Champernowne adaptive filter (CSS-FxAPCMAF). The emphasis of this research lies in robustness in environments with correlated input and impulsive noise. Simulation results demonstrate that the proposed algorithm can maintain a convergence rate while exhibiting smaller steady-state misalignment compared to existing algorithms, ensuring superior performance.

关键词： Automation Simulation Noise Adaptive filters filtering algorithms Control systems Robustness Steady-state Convergence

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Signal Optimization and Noise Reduction Based on Frequency Control in Acoustic Imaging Instruments

Signal Optimization and Noise Reduction Based on Frequency C...

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International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Zuyang Cao Xin Zhang Junkang Bao Hangzhou Crysound Electronics Co. Ltd. Hangzhou Zhejiang China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Papermaking machinery noise is the noise generated during the production process of a papermaking enterprise, which includes mechanical vibration and low-frequency noise. In the field test of paper-making enterprises, the noise range is 100–120 dB. According to the industry noise standard, the value of the noise can not be greater than 85 dB under the working condition of 8 hours. Therefore, to control the source of the noise, it is necessary to control the noise according to the noise mechanism of the equipment itself and block its propagation path in order to effectively reduce the noise of the factory. Visual acoustic imagers can quickly identify the sound source and introduce corresponding noise reduction measures in line with environmental protection. The aim of this study is to investigate the frequency control based signal optimization and noise reduction methods in acoustic imagers. U sing the Visual Acoustic Imager of CRY2600 series, the authors conducted experiments in mechanical air noise and collision vibration noise environments to evaluate the effects of different noise environments, filter types, dynamic frequency tuning strategies and signal processing algorithms on signal optimization and noise reduction. The results show that both low-pass and high-pass filters are effective in improving the signal-to-noise ratio in a specific frequency range, and the dynamic frequency tuning strategy performs better in improving the signal quality compared to the static tuning strategy. Both wavelet threshold denoising and generative adversarial network denoising algorithms perform well in different noise environments (wavelet threshold denoising improves the signal strength from 50dB to 70dB in a mechanical air noise environment, with a 20dB improvement in the signal-to-noise ratio), significantly improving the signal strength. The research results show that combining multiple noise reduction strategies can effectively improve the overall performance of the acous

关键词： Vibrations Visualization Heuristic algorithms Noise Noise reduction Signal processing algorithms filtering algorithms Acoustics Tuning Optimization

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Local Community Detection from Noisy Graph Streams

Local Community Detection from Noisy Graph Streams

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Big Data & Artificial Intelligence & Software Engineering (ICBASE), International Conference on

作者： Han Yang Lingxiang Wang Qingren Wang Huabin Wang Yiwen Zhang Hong Zhong Dengcheng Yan School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

The demand for real-time graph analysis has encouraged the research of online community detection methods. However, these methods often assume clean data, which is uncommon in reality. How to further improve the performance and robustness of online community detection for real-world networks has garnered the great attention. In this paper, we propose NgsLCD, an algorithm that identifies valid edges in noisy streams to expand communities and mitigate noise effects. It also uses a node-community similarity metric to filter out incorrectly added nodes. Tests on real networks show NgsLCD reduces noise impact and maintains robust detection performance across varying noise rate.

关键词： Image edge detection Noise filtering algorithms Robustness Real-time systems Noise measurement Detection algorithms Streams Software engineering Noise level

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Empirical Analysis of Feature Selection Techniques for Optimal Feature Set Identification in Android Malware Detection

Empirical Analysis of Feature Selection Techniques for Optim...

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International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Atul Chambyal Aman Kumar Sharma Department of Computer Science Himachal Pradesh University Shimla India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Android is facing an exponential surge in malware, and legacy malware detection systems are ineffective in detecting new malware. Machine learning techniques aid in developing more effective malware detection systems, but high-dimensional datasets can pose a challenge. Feature selection is the process of pinpointing and choosing the most relevant features from a dataset to enhance model performance and decrease computation time. Filter methods, regardless of machine learning models, are effective for feature selection. This article reviews different filter methods, compares their predictive accuracy, and provides practical recommendations for using feature selection in malware detection. An empirical evaluation is presented on the selected Drebin dataset, comparing common filter methods selected from a detailed literature review. Various machine learning algorithms receive feature subsets selected from diverse filter methods to assess their performance. ReliefF outperformed other methods, random forest achieving the highest accuracy.

关键词： Accuracy Machine learning algorithms Computational modeling filtering algorithms Feature extraction Grid computing Malware Surges Random forests Systematic literature review

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SOSA-based SSA-BP-PID temperature control of polyethylene cross-linked cable extruder

SOSA-based SSA-BP-PID temperature control of polyethylene cr...

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Electrical Engineering and Control Science (IC2ECS), International Conference on

作者： Yunan Wang Xindong Zhang College of Electronic Science & Engineering JiLin University ChangChun China

ISBN: (数字)9798331510107

ISBN: (纸本)9798331510114

Extruder as an indispensable and important machinery in polyethylene cross-linked production line, its temperature system is a system with large hysteresis and nonlinear. PID algorithm is the most common algorithm for the temperature control system of extruder, which has a large degree of freedom of adjustable parameters and requires debugging experience and manual calibration. In this paper, an SSA-BP-PID temperature control system algorithm based on self-occluded sliding average filtering (SOSA) is proposed. The Back Propagation (BP) algorithm improves the flexibility of PID tuning, while we use Sparrow Search Algorithm (SSA) algorithm to optimize the initial value of BP to make it more stable. In addition to avoid the fading jitter phenomenon of SSA-BP-PID, we propose the SOSA method to attenuate the oscillation phenomenon. The simulation results show that the SOSA-based SSA-BP-PID temperature control system for cross-linked cable extruder effectively reduces the fading jitter phenomenon. After adding SSA optimization algorithm, the amount of overshoot decreases from 4.76% to 3.44%, and the adjustment time is shortened by 30.7%. Additionally, the adjustment time is reduced by 53.28s based on SOSA-SSA-BP-PID, and the amount of overshoot can be reduced to 0.27%.

关键词： Fading channels Polyethylene filtering Simulation Jitter filtering algorithms Stability analysis Temperature control Tuning Thermal stability

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Anti-Occlusion Scale-Adaptive Correlation Tracking

Anti-Occlusion Scale-Adaptive Correlation Tracking

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Zhuanyang Chen Linjie Yang Yuan Zhang Luping Wang School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Target tracking at high-speed conditions is highly desirable for embedded systems, such as visual navigation. However, existing methods face challenges in achieving real-time processing due to algorithm complexity and computational limitations. To address this issue, we propose an anti-occlusion scale-adaptive correlation tracker (OSCT) based on a Kernelized Correlation Filter (KCF), which considers tracking confidence and multiple features in embedded systems. Specifically, we employ a discriminative correlation filter to estimate the scale of the tracking target. Subsequently, our tracker dynamically adjusts the learning rate by evaluating the confidence of tracking results. Moreover, the OSCT uses a re-detector to re-detect the target in case of tracking failure. Instead of relying on a single feature, our method integrates multiple features to address variation and occlusion in tracking objects. Experimental results demonstrate that: 1) OSCT achieves an average precision of 0.778 at 20 pixels, representing an improvement of over 8% compared to other high-speed trackers. 2) The average running speed of OSCT is 32 FPS, outperforming LCT (26 FPS). Therefore, our approach is well-suited for long-term tracking on embedded platforms.

关键词： Visualization Target tracking Correlation Embedded systems Navigation Image processing Machine learning filtering algorithms Robustness Real-time systems

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On Adaptive Feedback Active Noise Control Systems With Online Adaptation of Secondary Path Estimation Filter

On Adaptive Feedback Active Noise Control Systems With Onlin...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Muhammad Tahir Akhtar Department of Electrical and Computer Engineering School of Engineering & Digital Sciences Nazarbayev University Astana Kazakhstan

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

This paper focuses on identifying the secondary path (SP) in feedback active noise control (FBANC) systems during online operation. In FBANC, it's not feasible to install a reference microphone for capturing the reference signal needed for the (adaptive) active noise control (ANC) filter. Consequently, an appropriate reference signal is required to be electronically generated, necessitating an accurate estimation of the SP. The accuracy of SP estimation (SPE) directly impacts the stability and noise reduction capabilities of ANC systems. Building upon prior work that utilized two adaptive filters; one for ANC and another for SPE; this paper presents a method with a similar structure. The key idea in this paper is to tailor a generalized sigmoid function for developing a variable step-size (VSS)-based adaptive algorithm for (adaptive) ANC filter. The proposed method exhibits improved noise reduction performance as well as good SPE performance, as evidenced by the detailed numerical results provided in the paper.

关键词： Accuracy Simulation Noise reduction Noise Adaptive filters Estimation filtering algorithms

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