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Error Characteristic Analysis and filtering algorithm for GNSS Time-Series Data

SENSORS 2025年第2期25卷 361-361页

作者： Zhang, Hongli Chen, Yijin Li, Kemeng Wang, Yinggang China Univ Min & Technol Beijing Coll Geosci & Surveying Engn Beijing 100083 Peoples R China

Under regional environmental conditions such as open-pit mines and construction sites, there are usually fixed GNSS measurement points. Around these fixed stations, there are also mobile GNSS measurement modules. These mobile measurement modules offer advantages such as low power consumption, low cost, and large data volume. However, due to their low accuracy, these modules can only provide approximate positions as monitoring data, such as for vehicle management in open-pit mines. To extract more information from the existing large volume of low-accuracy data, it is necessary to process these low-accuracy data. Under conditions of the same time and space in a small area, factors affecting measurement accuracy can be comprehensively considered. By analyzing the temporal GNSS data within the same spatiotemporal small region and understanding the variation patterns of measurement errors, a general equation for measurement error variation can be formulated. Using filtering methods, the data quality can be improved. Through the analysis of the experimental data in this study, it was found that the variation patterns of measurement data obtained by devices of the same accuracy during the same time period are generally consistent. After applying filtering methods, the measurement accuracy of each station improved by up to approximately 95.9%, with a minimum improvement of approximately 84.4%. Under the condition of a 95% confidence level, the reliability increased by up to approximately 73.2%, with a minimum improvement of approximately 58.2%. These experimental results fully demonstrate that under regional spatiotemporal conditions, the temporal data obtained by GNSS measurement devices with similar accuracy exhibit similar error distribution patterns. Applying the same filtering method can significantly improve the accuracy and reliability of measurement data.

关键词： time series data filtering algorithm error compensation

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filtering algorithm of Airborne Doppler Lidar Measurements for Improved Wind Estimation

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TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES 2015年第3期58卷 149-155页

作者： Misaka, Takashi Nakabayashi, Fabio K. Obayashi, Shigeru Inokuchi, Hamaki Tohoku Univ Frontier Res Inst Interdisciplinary Sci Sendai Miyagi 9808577 Japan Tohoku Univ Inst Fluid Sci Sendai Miyagi 9808577 Japan Japan Aerosp Explorat Agcy Inst Aeronaut Technol Tokyo 1810015 Japan

In this paper, we describe a filtering algorithm for removing the error of wind velocity arises in airborne Doppler lidar measurements. The algorithm is based on the Kalman filter with a simplified Kalman gain, which assumes zero variance for correct wind velocity and infinite variance for incorrect wind velocity. The algorithm is applied to 17,487 seconds of airborne Doppler lidar measurements, where a sequence of measurements along the lidar's measurement range is obtained every one second. The reduction of incorrect wind velocity is evaluated at the distance where correct wind velocity exists at least 20-30% of the time out of all measurements. The average standard deviation of filtered wind velocity at the above mentioned distance results in 17.2% of the original value, which is similar magnitude to correct measurements.

关键词： filtering algorithm Airborne Doppler Lidar Atmospheric Turbulence

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Application of a territorial-based filtering algorithm in turbomachinery blade design optimization

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ENGINEERING OPTIMIZATION 2017年第2期49卷 216-234页

作者： Bahrami, Salman Khelghatibana, Maryam Tribes, Christophe Lo, Suk Yi von Fellenberg, Sven Trepanier, Jean-Yves Guibault, Francois Polytech Montreal Dept Mech Engn Montreal PQ Canada Andritz Hydro Canada Inc R&D Div Pointe Claire PQ Canada Polytech Montreal Dept Comp Engn Montreal PQ Canada

A territorial-based filtering algorithm (TBFA) is proposed as an integration tool in a multi-level design optimization methodology. The design evaluation burden is split between low-and high-cost levels in order to properly balance the cost and required accuracy in different design stages, based on the characteristics and requirements of the case at hand. TBFA is in charge of connecting those levels by selecting a given number of geometrically different promising solutions from the low-cost level to be evaluated in the high-cost level. Two test case studies, a Francis runner and a transonic fan rotor, have demonstrated the robustness and functionality of TBFA in real industrial optimization problems.

关键词： filtering algorithm multi-level design optimization blade shape optimization

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Distance protection based on a variable window length filtering algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2004年第9期26卷 669-679页

作者： Funk, AT Malik, OP Karwendelstr. 7 82049 Pullach Germany

Voltage and current phasors of standard distance protection filtering algorithms are estimated based on a full cycle window, resulting in a post-fault impedance estimate within one cycle after fault inception. Shorter data window lengths correspond to faster impedance estimates and thus faster line protection, but compromise security. In order to retain the reliability of full cycle filtering algorithms and to detect at least close faults more quickly than full cycle filtering algorithms, a variable filter length phasor estimation including variable trip area setting is proposed in this paper. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： distance protection filtering algorithm phasor estimation digital transmission-time protection

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A parametric filtering algorithm for the graph isomorphism problem

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CONSTRAINTS 2008年第4期13卷 518-537页

作者： Sorlin, Sebastien Solnon, Christine Univ Lyon 1 LIRIS CNRS UMR 5205 F-69622 Villeurbanne France

We introduce a new filtering algorithm, called IDL(d)-filtering, for a global constraint dedicated to the graph isomorphism problem-the goal of which is to decide if two given graphs have an identical structure. The basic idea of IDL(d)-filtering is to label every vertex with respect to its relationships with other vertices around it in the graph, and to use these labels to filter domains by removing values that have different labels. IDL(d)-filtering is parameterized by a positive integer value d which gives a limit on the distance between a vertex to be labelled and the set of vertices considered to build its label. We experimentally compare different instantiations of IDL(d)-filtering with state-of-the-art dedicated algorithms and show that IDL(d)-filtering is more efficient on regular sparse graphs and competitive on other kinds of graphs.

关键词： global constraint graph isomorphism filtering algorithm

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A method for weighing broiler chickens using improved amplitude-limiting filtering algorithm and BP neural networks

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Information Processing in Agriculture 2021年第2期8卷 299-309页

作者： Weihong Ma Qifeng Li Jiawei Li Luyu Ding Qinyang Yu Beijing Research Center for Information Technology in Agriculture Beijing 100097China National Engineering Research Center for Information Technology in Agriculture Beijing 100097China Key Laboratory of Agri-informatics Ministry of AgricultureBeijing 100097China Beijing Engineering Research Center of Agriculture Internet of Things Beijing 100097China

Broiler chickens are traditionally weighed by steelyard or platform scale,which is timeconsuming and *** chickens usually exhibit stress-related behavior during *** 3D camera-based weighing system for broiler chickens can only weigh the broiler chicken in the monitoring ***,it makes poor weight prediction due to poor segmentation especially when the broiler chicken is flapping its *** solve these issues,we developed one simple and low-cost weighing system with high stability and accuracy.A validity value extraction method from dynamic weighing was ***,an improved amplitude-limiting filtering algorithm and a BP neural networks model were developed to avoid accidental *** BP neural networks model used daily weight gain,day-age,average velocity,and the weight data after filtering algorithm as the input *** weighing system was tested in a commercial Beijing Fatty Chickens house with Beijing Fatty *** tested thirteen groups of Beijing Fatty Chickens of different weights,from 500 g to 1800 g in intervals of 100 g,using the three different methods:no filtering algorithm or BP neural networks,only the improved amplitude-limiting filtering algorithm and a hybrid of the improved amplitude-limiting filtering algorithm and BP neural *** results showed that the hybrid algorithm had a better performance in minimizing the error,lowering from the original 6%down to 3%.The accurate weight data was transmitted to the remote service platform for further decision-making,such as activity analysis,feeding management,and health alerts.

关键词： Weighing of broiler chickens Improved amplitude-limiting filtering algorithm BP neural networks Dynamic weighing

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A Cauchy perturbation cuckoo search particle filtering algorithm for remaining useful life prediction of lithium-ion battery considering capacity regeneration

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INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE 2023年第10期18卷

作者： Liang, Yongjian Wang, Rukun Qu, Guanglong Zhou, Zijian Liu, Yun Yan, Wenjun Liaoning Univ Sch Informat Shenyang 110000 Liaoning Peoples R China Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621000 Peoples R China Southeast Univ Sch Integrated Circuits Nanjing 210096 Peoples R China Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China

The remaining useful life prediction of the lithium-ion battery can evaluate the battery's reliability, identify the occurrence of faults, and reduce battery risks. In this study, the particle filtering algorithm is employed along with the introduction of the Cauchy perturbation factor to enhance the local optimization capability of the cuckoo search algorithm. The improved cuckoo search optimization algorithm is utilized to transfer particles from prior distribution areas to the maximum likelihood area, resulting in the development of the Cauchy perturbation cuckoo search particle filtering algorithm. To achieve high-precision prediction of the remaining useful life, an attenuation model is established, taking into account the complex capacity regeneration phenomenon that occurs after a long period of resting of the lithium-ion battery storage. This model includes three types of capacity: underlying, recovery, and surface capacity. The experimental results, based on an aging dataset from the University of Maryland, demonstrate that the suggested algorithm provides clear advantages over widely used particle filtering and unscented particle filtering algorithms in terms of estimation accuracy. Additionally, it exhibits a fast convergence rate and low resampling rate, further enhancing its benefits.

关键词： Remaining useful life Maximum likelihood area Cauchy perturbation factor Local optimization Cauchy perturbation cuckoo search particle filtering algorithm Capacity regeneration phenomenon

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A filtering algorithm for Marine Environmental Time Series Monitoring Data Based on Kinect Depth Information

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JOURNAL OF COASTAL RESEARCH 2020年第Sup1期000卷 762-765页

作者： Wei, Meng Ma, Ge Zhengzhou Normal Univ Coll Informat Sci & Technol Zhengzhou 450044 Peoples R China

In order to reduce the running time and computational cost of data filtering algorithm, a data filtering algorithm for marine environmental time series monitoring based on Kinect depth information was put forward. Firstly, the depth information was collected through the imaging principle of Kinect device. Secondly, the weighted mean algorithm was used to improve the stability of depth images by continuous multi-frame depth images in time. On this basis, the corresponding color image was used as a guide to fill the holes in the depth image according to the constraints of color consistency. Finally, the classical median filtering algorithm was used to smooth the depth image and remove noise. Thus, the time series monitoring data of marine environment based on Kinect depth information was filtered. Experimental results show that the proposed algorithm can effectively reduce the running time and computational overhead.

关键词： Kinect depth information marine environmental time series monitoring data filtering algorithm

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Selfish node filtering algorithm based on opportunity network 27

Selfish node filtering algorithm based on opportunity networ...

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27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Yan, Kun Hu, Hao Xu, Gang Wang, Yuqi Zhang, Gaofeng Li, Lijie Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China

ISBN: (纸本)9798350349184;9798350349191

The existing opportunistic network routing algorithms assume that nodes do not exhibit selfish behavior. In a well-cooperating network, these algorithms can effectively deliver messages. However, when nodes behave selfishly, the efficiency of these algorithms decreases. To address this issue, this paper proposes a filtering algorithm of Selfish Node(FASN).This algorithm filters selfish nodes by reducing the transmission probability of selfish nodes. Additionally, to alleviate network congestion, a new ACK confirmation mechanism is proposed. This mechanism not only removes redundant messages that have already been delivered but also deletes messages with a survival rate of 0. Finally, node differentiation punishment is achieved based on the number of times a node is added to a blacklist. Experimental results demonstrate that the FASN algorithm is suitable for opportunistic networks with high security requirements. Moreover, it effectively filters out selfish nodes and outperforms the CDEC algorithm and several classical routing algorithms in terms of delivery rate, overhead, and average delay.

关键词： opportunistic networks selfish node filtering algorithm blacklist differentiation punishment

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A Point Clouds filtering algorithm Based on Grid Partition and Moving Least Squares

A Point Clouds Filtering Algorithm Based on Grid Partition a...

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International Conference on Modern Hydraulic Engineering (CMHE)

作者： Liu Changjun Li Jian Zhang Shunfu Ding Liuqian China Inst Water Resources & Hydropower Res A-1 Fuxing Rd Beijing 100038 Peoples R China Wuhan Univ Sch Remote Sensing Informat Engn Wuhan 430079 Peoples R China

A point clouds filtering algorithm is presented based on Grid Partition using Dynamic Quad Tress and Moving Least Squares. First, points are partitioned reasonably and corresponding Dynamic Quad Trees indices are established. Second, points in grids are utilized to fit a DEM reference plane using moving least squares technology. Finally, ground points are separated from those non-ground ones if they are positioned above the reference plane and have a distance to the plane exceeding threshold value. Experiments show that this filtering algorithm is of high precision and identify ground points effectively without losing detailed topography information. (c) 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Society for Resources, Environment and Engineering

关键词： Lidar point clouds filtering algorithm dynamic quad trees spatial index moving least squares

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