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A Grain Output Combination Forecast Model Modified by data fusion algorithm

JOURNAL OF INTELLIGENT SYSTEMS 2018年第2期27卷 303-315页

作者： Wan, Xiang Liu, Bing-Xiang Xu, Xing Jingdezhen Ceram Inst Sch Informat Engn Jingdezhen 333403 Jiangxi Peoples R China

To deal with the lack of accuracy and generalization ability in some single models, grain output models were built with lots of relevant data, based on the powerful non-linear reflection of the back-propagation (BP) neural network. Three kinds of grain output models were built and took advantage of - particle swarm optimization algorithm, mind evolutionary algorithm, and genetic algorithm - to optimize the BP neural network. By the use of data fusion algorithm, the outcomes of different models can be modified and fused together, and the combination-predicted outcome can be obtained finally. Taking advantage of this combination model to predict the total grain output of China, the results showed that the total grain output in 2015 was a bit larger than the actual value of about 0.0115%. It was much more accurate than the three single models. The experimental results verify the feasibility and validity of the combination model.

关键词： BP neural network data fusion algorithm grain output

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3D Motion Tracking of the Shoulder Joint with Respect to the Thorax Using MARG Sensors and data fusion algorithm

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BIOCYBERNETICS AND BIOMEDICAL ENGINEERING 2020年第3期40卷 1205-1224页

作者： Barraza Madrigal, Jose Antonio Cantillo Negrete, Jessica Munoz Guerrero, Roberto Contreras Rodriguez, Lauro Armando Sossa, Humberto Inst Politecn Nacl Acad Fis Escuela Super Ingn Quim & Ind Extract Mexico City DF Mexico Inst Nacl Rehabil Div Res Med Engn Calzada Mexico Xochimilco 289 Mexico City DF Mexico Natl Polytech Inst Ctr Res & Adv Studies Elect Engn Dept Bioelect Sect Mexico City DF Mexico Inst Politecn Nacl Ctr Invest Comp Lab Robot & Mecatron Mexico City DF Mexico Tecnol Monterrey Unidad Guadalajara Zapopan Jalisco Mexico Inst Politecn Nacl ESIQIE Unidad Profes Adolfo Lopez Mateos Edificio 6 Ciudad De Mexico 07738 Mexico Av Juan de Dios Batiz Mexico City 07738 DF Mexico

A method for performing 3D motion tracking of the shoulder joint with respect to the thorax, using MARC sensors and a data fusion algorithm, is proposed. Two tests were done: 1) qualitative and quantitative analysis of the response of the sensors, static position and during motion, with and without the proposed data fusion algorithm;2) motion tracking of the shoulder joint with the upper arm, the thorax, and the shoulder joint respect to the thorax. Qualitative analysis of experimental results showed that despite slight variations regarding the evaluated motion, these variations did not have repercussions on the estimated orientation. Quantitative analysis showed that the estimated orientation did not exhibit significant variations, in five minutes, such as drift errors (about 0.1 degrees in static position and less than 1.8 degrees during motion), variations due to noise or magnetic disturbances (RMSE less than 0.04 degrees static position and less than 1 degrees during motion);no singularity problems were reported. The main contributions of this research are a multisensor data fusion algorithm, which combines the complementary properties of gyroscopes, accelerometers, and magnetometers in order to estimate the 3D orientation of two body segments separately and with respect to another body segment considering the spatial relationship between them;and a method for performing 3D motion tracking of two body segments, based on the estimation of their orientation, including motion compensation. The proposed method is applicable to monitoring devices based on IMU/MARG sensors;the performance was evaluated using a customized motion analysis system. (C) 2020 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.

关键词： Shoulder joint and thorax 3D motion tracking Orientation estimation MARC sensors data fusion algorithm

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An on-line measuring fusion model of lumber moisture content based on data fusion algorithm

An on-line measuring fusion model of lumber moisture content...

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5th International Conference on Wavelet Analysis and Pattern Recognition

作者： Li, Jian Sun, Li-Ping Liu, De-Sheng NE Forestry Univ Coll Mech & Elect Harbin 150040 Peoples R China

ISBN: (纸本)9781424410651

Lumber moisture content is a key parameter for regulating and controlling wood drying process. Its precision directly affects the drying quality, cost and drying time. In this paper a fusion model capable of on-line measuring lumber moisture content is presented. Models for predicting lumber moisture content are established using both back-propagation neural networks (BPNN) and dynamical recurrent Mural networks (DRNN). Furthermore, the two models are integrated by arithmetic average and recursive estimation algorithm. The simulation result, which is worked out by experimental data, shows that fusion model have a higher predictive precision than any one of BP Mural network's and DRNN's, therefore, this method is proved to be feasible.

关键词： lumber moisture content data fusion algorithm neural network fusion model

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Multi-sensors data fusion algorithm of Improved Dempster-Shafer Evidence Reasoning

Multi-sensors Data Fusion Algorithm of Improved Dempster-Sha...

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International Conference on Graphic and Image Processing (ICGIP)

作者： Wang Ming-fang Zhu Ming-e Yu Shao-jun Cent S Univ Forestry & Technol Sch Comp Sci & Technol Changsha 410004 Hunan Peoples R China

ISBN: (纸本)9780819489326

An improved multi-sensor data fusion algorithm based on Dempster-Shafer evidence theory and a criterion of the object evaluation are presented in this paper. The algorithm and the criterion investigate the monitor data of the indoor air that is the research object, and evaluate the quality grade of the indoor air. Experiment shows that the improved multi-sensor data fusion algorithm based on the Dempster-Shafer reasoning and the resulting evaluations are correct and solve the uncertainty problem which is produced in the multi-sensor information process.

关键词： improved Dempster-Shafer evidence reasoning data fusion algorithm multi-sensors

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A Grouping based Prioritized Sensor data fusion algorithm for deciding the State of a Coal Mine

A Grouping based Prioritized Sensor data fusion Algorithm fo...

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International Conference on Advances in Computing, Communications and Informatics ICACCI

作者： Sarkar, Anibroto Banerjee, Indrajit Indian Inst Engn Sci & Technol Dept Informat Technol Sibpur 711103 Howrah India

ISBN: (纸本)9781479987924

The main constraints of a wireless sensor network are limited battery power and short lifetime. One of the main reasons of energy consumption is the data transmission. Each node senses the data and sends them over to the base station. The sensor data fusion reduces the volume of message transmission and makes the network energy efficient. In this paper, we have presented a data fusion algorithm which minimizes the computation cost, communication cost and in the same way it reduces the consumption of energy. The algorithm derives the state of the network using the concept of priority of the sensors. The proposed algorithm gives a better false alarm rate than the existing data fusion algorithm used in the coal mine.

关键词： data fusion algorithm Wireless Sensor network (WSN) Clustering algorithm

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Research on data fusion algorithm for Attitude Detection Systems Based on MEMS and Magnetoresistive Sensors 9

Research on Data Fusion Algorithm for Attitude Detection Sys...

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9th International Conference on Advanced Infocomm Technology (ICAIT)

作者： Wang, Xiang Bai, Ru Cui, Xiaoyang Wu, Tao Qian, Zhenghong Hangzhou Dianzi Univ Ctr Integrated Spintron Devices Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538636282

The attitude detection system based on MEMS and magnetoresistive sensors is widely used in a variety areas. The magnetoresistive sensor acts as an auxiliary sensor to correct the measured value of MEMS inertial sensor. It is necessary to design an appropriate data fusion algorithm to process multiple sensor data. According to the output characteristics of each sensor, the data fusion algorithm take advantage of each sensor and reduce the unreliability of a single sensor in the measurement process to obtain the optimal attitude estimation. The performance of data fusion algorithm will affect the accuracy and stability of whole system. Focused and reviewed in this paper are the present situation and development trend of data fusion algorithm for attitude detection system based on MEMS and magnetoresistive sensors.

关键词： attitude detection magnetoresistive sensors MEMS inertial sensor multiple sensor data fusion algorithm

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Multi-channel detection of dopamine and glucose utilizing graphene field effect transistor electrochemical sensor and efficient data fusion algorithm

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JOURNAL OF ELECTROANALYTICAL CHEMISTRY 2023年 950卷

作者： Xie, Ziyu Sun, Peng Cao, Shengli Yang, Yongkang Wang, Xuyang Xiao, Gang Yan, Gangping Bi, Jinshun Ji, Jing Yue, Zhao Nankai Univ Dept Microelect Tianjin 300350 Peoples R China Xidian Univ Sch Mechanoelect Engn Xian 710071 Peoples R China Inst Microelect Chinese Acad Sci Beijing 100029 Peoples R China Univ Chinese Acad Sci Sch Microelect Beijing 100049 Peoples R China Optoelect Sensor & Sensing Network Technol Tianjin Key Lab Tianjin 300350 Peoples R China Nankai Univ Smart Sensing Interdisciplinary Sci Ctr Tianjin 300350 Peoples R China

Schizophrenia, a severe neurological disorder, is linked to aberrations in dopamine (DA) and glucose levels. While numerous methods have been developed for the sensitive and selective detection of either DA or glucose individually, there remains a challenge in achieving simultaneous detection of both with a single platform. To address this, we designed a graphene field effect transistor (GFET) based electrochemical sensor, augmented with 11-mercaptoundecanoic acid-gold nanoclusters (MUA-AuNCs) and pyrene-1-boronic acid (PBA) for enhanced DA and glucose detection. MUA-AuNCs and PBA improved selectivity and sensitivity towards DA and glucose respectively. Moreover, we incorporated a unique data fusion algorithm based on a least squares method. Utilizing a dual-channel sensor setup, this algorithm corrects interference by leveraging accurate DA readings from one channel to compute precise glucose concentrations in mixed solutions, thus ensuring high detection accuracy. This sensor displayed exceptional performance in simultaneous DA and glucose detection, addressing prevalent issues in current methods. Our approach not only has potential to improve schizophrenia monitoring but also provides insights for electrochemical sensor design and optimization.

关键词： Graphene field effect transistor Dopamine Glucose Multi-channel detection Electrochemical Sensing data fusion algorithm

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Stock Market Investment Behavior Based on Behavioral Finance Based on data fusion algorithm

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IETE JOURNAL OF RESEARCH 2022年

作者： Yuan, Feng Zhan, Hui JiLin Engn Normal Univ Sch Econ & Trade Changchun 130052 Jilin Peoples R China

The stock market is developing rapidly and the study of its investment behavior is indispensable. In this paper, based on the framework of fusion algorithm, information on various investor behaviors is federated based on IoT technology. Psychological experimental method is used to collect experimental sample data in the form of questionnaires. And based on the theoretical knowledge of behavioral finance, some investment recommendations on individual investors' investment behavior are proposed. The results of this empirical study show that when individual investors face investment risks, the psychological bias of their perceptions is unfavorable to most of them. And the results prove that more than 50% of them are influenced by their own limited cognition.

关键词： data fusion algorithm behavioral finance Stock Market investment behavior

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Wireless Network Monitoring System for River Ice Environment Based on a data fusion algorithm

Wireless Network Monitoring System for River Ice Environment...

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作者： Zhen-yu ZHONG Li ZHANG Jian-min QIN Ze-yu ZHONG Li-qin CUI Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan University of Technology China Mobile Group Co. Ltd. State Grid Taiyuan Power Supply Company

There are still quite a few problems in river ice environment monitoring by remote monitoring network, such as the increase of the various sensor nodes and network capacity overload due to the dense deployment, and the decrease of the life expectance of the network. In view of this, the improved K-means data fusion algorithm was proposed to fuse a variety of data by a novel self-developed sensor. Furthermore, the resilient BP network was employed to build a data model database, so as to identify the overall river ice environment at the back-end remotely in real time. Simulation verification and comparison test results show that the proposed algorithm can achieve efficient and accurate data transmission by various sensors and the existing sensor network during the real-time monitoring of the river ice environment.

关键词： River ice Wireless network monitoring data fusion data fusion algorithm

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Robot Navigation by a Novel Multi-sensor data fusion algorithm

Robot Navigation by a Novel Multi-sensor Data Fusion Algorit...

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第二届全国几何设计与计算学术会议

作者： Xiong Li Zongchang Xu Kai Wang Department of Command and Administration Armored Force Engineering Institute

In order to be able to interact with its environment correctly,a robot require high-precision navigation over various *** involves the ability to determine a robot's position relative to objects (stationary or moving) in the environment,and to interact with them ***,multiple sensors are used as redundant computation channels to tolerate certain types of error,incompleteness, inaccuracy,and/or tardiness in the data supplied by individual system elements such as sensors or processors. data fusion in multi-sensor systems is investigated by numerous *** problem of "voting" or, more generally,integrating results from multiple computations has been studied by computer

关键词： multi sensor data fusion algorithm fuzzy similarity robot navigation

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