检索结果-内蒙古大学图书馆

3rd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC)

作者： Piao, Xinan Jiang, Wenmei Hu, Chunyi Cai, Dongxin Dongguan City Univ Sch Artificial Intelligence Dongguan Peoples R China

ISBN: (纸本)9798350352634;9798350352627

Against the backdrop of the intensifying aging population in China, the issue of preventing falls among the elderly has become increasingly prominent. Statistics indicate that falls are one of the main causes of accidental injuries and deaths among the elderly, with the risk of falling being directly proportional to the age of the elderly. Due to the large range of activities of the elderly, methods that require the deployment of detection equipment in fixed locations have significant limitations. Multi-sensor detection devices are not easily portable and can impact the daily activities of the elderly. Therefore, this study proposes a wearable smart belt system aimed at addressing the high risk of falls and the difficulty of emergency rescue for the elderly. The accuracy of the device has been verified through experiments, capable of accurately detecting falls and correctly triggering the alarm function when a fall occurs, with the alarm function operating normally.

关键词： kalman filter algorithm Fall Detection Internet of Things Wireless Communication GPS Positioning

来源：评论

学校读者我要写书评

暂无评论

Predicting aircraft taxiing estimated time of arrival by cluster analysis

引用

IET INTELLIGENT TRANSPORT SYSTEMS 2022年第2期16卷 252-262页

作者： Tang, Xinmin Ji, Xiaoqi Liu, Jinan Nanjing Univ Aeronaut & Astronaut Civil Aviat Coll Nanjing 211100 Peoples R China

In order to predict the aircraft taxiing estimated time of arrival (ETA) to reduce scene conflicts and improve the operating efficiency of airports, the kalman filter algorithm is employed to preprocess historical trajectory data for an airport scene. For the first time, in order to measure the distance between trajectory samples, the aircraft taxiing period and the number of aircraft in a scene are used as sample features for aircraft taxiing ETA prediction. The dynamic time warping algorithm is employed to extract the different features of the trajectory. The Euclidean distance between two sample features is taken as their similarity. The initial clustering centre is determined based on the divided difference maximum principle by using the K-means algorithm to cluster samples and selecting the cluster with the highest matching degree according to the time period of the aircraft under planning and the number of aircraft operating in the scene. The trajectory sequence for the sample at the cluster centre and the static path planned by the tower are combined to predict the aircraft taxiing ETA. The accuracy of this method at predicting the aircraft taxiing ETA was demonstrated in simulations by comparing and analysing actual trajectory data with predicted taxiing ETA.

关键词： aircraft taxiing estimated time aircraft taxiing ETA prediction historical trajectory data actual trajectory data predicted taxiing ETA dynamic time warping algorithm path planning kalman filter algorithm cluster analysis sample features airports initial clustering centre time-of-arrival estimation kalman filters K-means algorithm cluster samples Euclidean distance aircraft airport scene difference maximum principle

来源：评论

学校读者我要写书评

暂无评论

Wind power prediction based on PSO-kalman

引用

ENERGY REPORTS 2022年 8卷 958-968页

作者： Li, Daoqing Yu, Xiaodong Liu, Shulin Dong, Xia Zang, Hongzhi Xu, Rui Qilu Univ Technol Shandong Acad Sci Sch Elect Engn & Automat Jinan 250353 Peoples R China State Grid Shandong Elect Power Co Econ & Technol Res Inst Jinan Peoples R China Huaneng JinanHuangtai Power Generat Co Ltd Jinan Peoples R China

Because of its clean and green, wind power is broadly used all over the world. Wind power is random and unstable, so wind power integration will inevitably bring great impact to power system. Accurate wind power prediction can effectively alleviate the impact caused by wind power uncertainty. In order to increase the accuracy of wind power prediction, this article uses paper swarm optimization algorithm (PSO) to improve the traditional kalman filter, and PSO-kalman wind power point prediction model is established. The proposed model solves the problem of low prediction accuracy of traditional kalman filter caused by observation noise and process noise. Finally, based on point prediction error, non-parametric kernel density estimation is used for interval prediction. By experimental simulation, by comparing the error evaluation indexes of point prediction and interval prediction, it can be found that the point prediction error of PSO-kalman is the smallest, indicating that PSO can effectively improve the prediction accuracy of kalman. On this basis, the interval prediction performance is also better than before. Moreover, the model proposed in this article converges fast and has better general applicability. (C) 2022 The Authors. Published by Elsevier Ltd.

关键词： Wind power prediction Particle swarm optimization algorithm (PSO) kalman filter algorithm Non-parametric kernel density estimation

来源：评论

学校读者我要写书评

暂无评论

Intelligent language analysis method for multi-sensor data fusion

引用

INTERNET TECHNOLOGY LETTERS 2024年第2期7卷

作者： Han, Tengxiao Huanghe Univ Sci & Technol Zhengzhou 450008 Peoples R China

Language intelligence analysis oriented to multi-sensor data fusion is of great significance for language analysis in real scenarios. On the one hand, intelligent language analysis technology can greatly improve the performance of applications such as information retrieval and machine translation, and provide technical support for semantic-level applications. On the other hand, each language has its own unique characteristics, and the advancement of the language system through language analysis technology is of great benefit to natural language analysis. In this letter, an intelligent language analysis method for multi-sensor data fusion is elaborated. Specifically, the kalman filter algorithm is combined to perform the first preprocessing filter fusion on multi-sensor data. Then, the deep learning model is used to design a language analysis model using Bidirectional Long-Short Memory Neural Networks (Bi-LSTM) to obtain deep fusion of multi-sensor data. In the experiment, the multi-sensors are used to collect real language data and public language datasets for verification, and the results show the effectiveness of the method proposed in this letter in terms of syntactic label classification.

关键词： data fusion kalman filter algorithm language analysis multi-sensors

来源：评论

学校读者我要写书评

暂无评论

Dynamic coordinated control strategy of a dual-motor hybrid electric vehicle based on clutch friction torque observer

引用

HELIYON 2024年第5期10卷 e27255页

作者： Xue, Qicheng Zhang, Xin Chen, Hongwei Yue, Meiling Teng, Teng Yu, Jiangbin Beijing Jiaotong Univ Sch Mech Elect & Control Engn Beijing Key Lab Powertrain Technol New Energy Vehi Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Mech Elect & Control Engn Beijing 100044 Peoples R China

The hybrid power system with dual motors and multiple clutches experiences significant torque fluctuation during mode switching process due to the different torque response characteristics of the motor and engine. To address this issue, this paper focuses on the estimation of clutch friction torque and the development of dynamic coordinated control strategies for the components. Firstly, based on the dynamic model of the novel dual-motor hybrid electric vehicle, a torque observer based on the kalman filter algorithm is developed to predict the friction torque generated in the clutch sliding friction stage. Secondly, the control strategies are developed for the mode switching process from single-motor to dual-motor and from dual-motor to parallel drive on a co-simulation platform. Thirdly, a power level Hardware-In-the-Loop test platform is built, and the performance of the designed control strategies is verified by the HIL platform. The results show that for the mode switching process from dual-motor to parallel drive, compared with the control strategy using the engine target speed, the control strategy based on engine idle speed proposed in this paper reduces the clutch sliding friction work and the maximum longitudinal jerk of the vehicle by 42.5% and 25.4%, respectively.

关键词： Clutch friction torque Dynamic coordinated control strategy Hybrid electric vehicle kalman filter algorithm Mode switching

来源：评论

学校读者我要写书评

暂无评论

An Online Multistep-Forward Voltage-Prediction Approach Based on an LSTM-TD Model and KF algorithm

引用

COMPUTER 2021年第8期54卷 56-65页

作者： Ni, Ye Xia, Zhilong Fang, Chunrong Chen, Zhenyu Zhao, Fangtong Nanjing Univ Nanjing Peoples R China Univ Akron Akron OH 44325 USA

We propose a multistep-forward voltage-prediction approach combining a long short-term memory time-distributed model and the kalman filter algorithm to improve prediction efficiency and reduce the demand for computing... 详细信息

关键词： Distributed algorithms kalman filters Recurrent Neural Nets LSTM TD Model KF algorithm kalman filter algorithm Prediction Efficiency Online Multistep Forward Voltage Prediction Approach Long Short Term Memory Time Distributed Model Computing Capability Computational Modeling Memory Management Predictive Models Prediction algorithms kalman filters

来源：评论

学校读者我要写书评

暂无评论

Wind load identification of lattice towers using multi-source heterogeneous monitoring data

引用

JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS 2023年第1期236卷

作者： Zhang, Qing Fu, Xing Lai, Tao Ren, Liang Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian 116023 Peoples R China Nanjing Tech Univ Coll Civil Engn Nanjing 211816 Peoples R China

Wind load is one of the governing design loads for lattice tower structures. However, such information is difficult to be measured directly, and the traditional indirect identification methods highly depend on the accuracy of finite element model and are limited to fluctuating wind loads. To solve this problem, a novel wind load identification method from limited multi-source heterogeneous monitoring data is proposed. First, the complex model of a lattice tower is simplified into a reduced-order model based on the similarity principle of dynamic characteristics. And then, limited strain and acceleration data are fused to reconstruct wind-induced responses and modal parameters based on kalman filter algorithm and mode-superposition method. Finally, the total wind loads, including both mean and fluctuating components, are obtained from identified modal parameters and modal responses. Numerical simulation of a lattice tower verified that the proposed method can reconstruct wind load and base reaction forces with high accuracy, and the anti-noise analysis shows that the proposed method has strong noise robustness. Moreover, the field test of a transmission tower during Typhoon Mangkhut was further carried out to validate the proposed method.

关键词： Wind load identification Lattice tower kalman filter algorithm Field test Reduced-order model

来源：评论

学校读者我要写书评

暂无评论

Dynamic self-calibration of time grating sensors based on self-adaptive kalman filter algorithm

Dynamic self-calibration of time grating sensors based on se...

引用

6th International Symposium on Precision Mechanical Measurements (ISPMM)

作者： Chen Ziran Chongqing Univ Technol Chongqing Key Lab Time Grating Sensing & Adv Test Minist Educ Engn Res Ctr Mech Testing Technol & Equipment Chongqing Peoples R China

ISBN: (纸本)9780819497925

As regarding the errors caused by mechanical installation and signal processing, a novel self-adaptive kalman filter algorithm is proposed. According to kalman filter recursion formula, the current value can be estimated with the last estimated value and the current measured value. Therefore, the kalman filter algorithm does not need recorder the past series of the estimated value and the current measured value, the calculated load is not too heavy to implement. The respond speed and the quality of time grating can be improved significantly. Experiment results prove the valid of the proposed method.

关键词： kalman filter algorithm time grating sensor self- adaptive

来源：评论

学校读者我要写书评

暂无评论

Thermodynamics-based measurement of the velocity of high-temperature smoke

引用

ARCHIVES OF THERMODYNAMICS 2023年第1期44卷 23-36页

作者： Wang, Haoyu China Fire & Rescue Inst Dept Fire Engn Nanyan 4 Beijing 102202 Peoples R China

In view of the high cost and difficulty of ensuring the accu-racy in the measurement of fire smoke velocity, the measurement system developed using platinum resistance temperature detectors and an 8-bit mi-crocontroller, is used to realize the fast measurement of high-temperature fire smoke velocity. The system is based on the thermodynamic method and adopts the kalman filter algorithm to process the measurement data, so as to eliminate noise and interference, and reduce measurement error. The experimental results show that the kalman filter algorithm can effec-tively improve the measurement accuracy of fire smoke velocity. It is also shown that the system has high measurement accuracy, short reaction time, low cost, and is characterized by high performance in the measurement of high-temperature smoke velocity in experiments and practice.

关键词： Thermodynamics Smoke Flow velocity Measurement kalman filter algorithm

来源：评论

学校读者我要写书评

暂无评论

Innovative reform strategy of artistic practice of university folk dance education based on information fusion technology

引用

APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2023年第1期9卷

作者： Zhou, Miao Hunan First Normal Univ Coll Mus & Dance Changsha 410205 Hunan Peoples R China

With the development of history, some folk dances are annihilated and lost in the inheritance. In order to protect and inherit national intangible cultural heritage and promote the construction of advanced socialist culture, this paper uses information fusion technology, combines national aesthetic personality, and refers to multi-factor theory, construction theory, and distillation theory to design and reform the art practice model of folk dance education. The data of dancers' skeletal joint points are collected by using multiple Kinect sensors, and the kalman filter algorithm is selected to establish the human skeletal motion model and fuse the data information of each joint point. Taking the hand_right and elbow_right joints as examples, it was found that the mean value of the error between the testers' joint trajectory and the template movement was reduced from 10mm to 4mm, and the mean value of the error between the joint angle and the template movement was reduced from 90 degrees to 35 degrees. Comparing the dance movement training effects and scores of the experimental group and the control group, it was found that the experimental group kicked the front and side legs an average of 70 times/minute, the middle jump height was improved by 10cm, and the average score was 3.33 points higher. This indicates that the integration of information fusion technology in the art practice of dance education can realize the practical innovation of college folk dance education and improve the comprehensive level of folk dance.

关键词： Information fusion technology Folk dance education kalman filter algorithm Multiple Kinect sensors Ethnic aesthetic personality

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：