检索结果-内蒙古大学图书馆

No-reference video quality assessment method based on spatio-temporal features using the elm algorithm

IET IMAGE PROCESSING 2020年第7期14卷 1316-1326页

作者： da Silva, Wyllian Bezerra Mikowski, Alexandre Casali, Rafael Machado Univ Fed Santa Catarina Lab Modelling & Data Anal LabMAD Florianopolis SC Brazil

This work presents an application of the extreme learning machine (elm) algorithm based on a single-hidden layer feedforward neural network for no-reference video quality assessment. The present research introduces an augmented version of elm through simple stop criteria, which proved the effectiveness of the video quality assessment method. The authors present empirical studies using LIVE video data base show that the proposed method delivers accuracy (Pearson's correlation coefficient) and monotonicity (Spearman's correlation coefficient) with subjective scores against no-reference, Joint Photographic Experts Group No-Reference, metric and full-reference metrics, for instance, peak signal-to-noise ratio, structural similarity (SSIM) and multi-scale-SSIM indexes, and the proposed method is suitable for quality monitoring of video transmission and reception system.

关键词： data compression feedforward neural nets feature extraction learning (artificial intelligence) video coding Pearson correlation coefficient Spearman correlation coefficient full-reference metrics quality monitoring video transmission reception system reference video quality assessment method spatio-temporal features elm algorithm extreme learning machine algorithm single-hidden layer feedforward neural network no-reference video quality assessment stop criteria joint photographic experts group no-reference LIVE video data base

来源：评论

学校读者我要写书评

暂无评论

Research on Fall Detection System of Wearable Devices Based on elm algorithm 3

Research on Fall Detection System of Wearable Devices Based ...

引用

IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Wang, Xiaolei Li, Donghao Zheng, Xiaowan Yan, Shuangjian Zhang, Qingfang Zhang, Jitao Cao, Lingzhi Zhengzhou Univ Light Ind Sch Elect & Informat Engn Zhengzhou Henan Peoples R China

ISBN: (纸本)9781538662434

The aging phenomenon in current society is getting more and more serious, and the health status of the elderly is lacing challenges. A fracture or other disease caused by a fall, or a fall due to a sudden illness, may result in serious consequences if not treated in time. According to the difference between fall and normal activities, this paper proposes a method for detecting human fall by elm based on inertial measurement unit. By placing the inertial measurement unit on the human body, the human acceleration and angular velocity data are sampled and the human body attitude is calculated. The elm training is performed on the human characteristic data to obtain the elm classification function, and the measurement data is classified by the elm classification function to determine whether it is in a falling state. The human fall experiment is carried out, and the result shows that the elm method can accurately detect the fall state of the human. The use and promotion of this method is of great significance for the treatment of falls and reduction of casualties.

关键词： fall detection wearable device elm algorithm IMU

来源：评论

学校读者我要写书评

暂无评论

A Novel Method for Recognizing Traffic Signs using Color and Texture Properties using the elm algorithm

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第12期13卷 55-62页

作者： Cao, Xiaoda Northeast Agr Univ Lab Management Dept Harbin 150030 Heilongjiang Peoples R China

Road accidents cause a lot of financial and human losses every year. One of the causes of these accidents is human error, and the driver ignores traffic signs. Therefore, accurate detection of these signs will help to increase the safety of drivers and pedestrians and reduce accidents. In recent years, much research has been done to increase the accuracy of panel recognition, most of which are problems that affect the diagnosis, such as adverse weather conditions, light reflection, and complex backgrounds. In the present study, considering the diversity of traffic signs' geometric shapes, the ngis detection part has been done using a torsional neural network. Then, in the feature extraction section, we used LBP and HOG techniques, and at the end, the section was identified and classified using the elm algorithm. The results obtained on 12569 images, 75% of which were used for training and 25% for experimentation, show that the accuracy of this research has improved by 95% compared to the essential work by 93%.

关键词： Traffic sign recognition torsional neural network HOG Feature LBP Feature elm algorithm

来源：评论

学校读者我要写书评

暂无评论

Research on Optimization Methods of elm Classification algorithm for Hyperspectral Remote Sensing Images

引用

IEEE ACCESS 2019年 7卷 108070-108089页

作者： Huang, Fang Lu, Jun Tao, Jian Li, Li Tan, Xicheng Liu, Peng Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Sichuan Peoples R China Texas A&M Univ High Performance Res Comp Texas A&M Inst Data Sci College Stn TX 77843 USA Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Hubei Peoples R China Chinese Acad Sci Aerosp Informat Res Inst AIR Beijing 100094 Peoples R China

In land-use classification of hyperspectral remote sensing (RS) images, traditional classification methods often experience large amount of datasets and low efficiency. To solve these problems, a fast machine-learning method, the extreme learning machine (elm) algorithm, was introduced. However, basic use of the elm usually encounters problems of unstable classification results and low classification accuracy. Hence, in this paper, optimization methods for elm-based RS image classification were mainly discussed and applied to solve the bottleneck problems. From the three perspectives of ensemble learning, making full use of image texture features, and deep learning, three classification optimization methods have been designed and implemented. The results show that: 1) To some extent, all the three methods can achieve a balance between classification accuracy and efficiency, i.e., they can maintain the advantage of elm algorithm in classification efficiency and speed while have better classification accuracy;2) The image texture feature optimization method (LBP-Kelm) solves the problem of unsatisfactory classification results experienced by the ensemble learning optimization method (Ensemble-elm) and further improves classification accuracy. However, the classification results are sensitive to the type of dataset;and 3) Fortunately, the optimization method combined with deep learning (CNN-elm) can meet the application needs of multiple datasets. Furthermore, it can also further improve classification accuracy.

关键词： Hyperspectral remote sensing elm algorithm ensemble learning texture features deep learning

来源：评论

学校读者我要写书评

暂无评论

Research on Measurement Method of Spherical Joint Rotation Angle Based on elm Artificial Neural Network and Eddy Current Sensor

引用

IEEE SENSORS JOURNAL 2021年第10期21卷 12269-12275页

作者： Hu, Penghao Tang, Chuxin Zhao, Linchao Liu, Shanlin Dang, Xueming Hefei Univ Technol Sch Instrument Sci & Optoelect Engn Hefei 230009 Peoples R China

This paper proposes a measurement method for the rotation angle of the spherical joint based on the extreme learning machine (elm) artificial neural network and four eddy current sensors. Aiming at the problems of small range and low accuracy in the early three-eddy-current angle measurement prototype, the position matching scheme of four eddy current sensors is researched, a new prototype is developed through simulation analysis, and elm neural network substitutes the previous generalized regression neural network (GRNN) for building a new measurement model. The modelling training and comparison test are completed in the self-developed high-precision angle calibration device. Experimental results show that the new prototype not only covers a +/- 20 degrees measurement range but also promotes measurement accuracy, and the standard deviation of the single-axis measurement drops to 3' within the range of 5 degrees-15 degrees. It provides a relatively high-precision measurement method for real-time, multi-axis active detection of spherical joint space rotation angle error.

关键词： Spherical joint eddy current sensor elm algorithm angle measurement

来源：评论

学校读者我要写书评

暂无评论

IoT-based approach to condition monitoring of the wave power generation system

引用

IET RENEWABLE POWER GENERATION 2019年第12期13卷 2207-2214页

作者： Qian, Peng Feng, Bo Zhang, Dahai Tian, Xiange Si, Yulin Brunel Univ London Dept Mech Aerosp & Civil Engn Uxbridge UB8 3PH Middx England Zhejiang Univ Ocean Coll Hangzhou 310058 Zhejiang Peoples R China

Accurate and reliable fault detecting plays a key role in application of grid-connected wave power generation systems. This study presents a novel IoT-based approach to condition monitoring of the wave power generation system, which has faster operating rate and lower hardware requirement. The compressed sensing (CS) method is adopted to compress the data, which aims to reduce the data uploaded to cloud platform;and then, the extreme learning machine (elm) algorithm is used to achieve the condition monitoring of wave power generation system in cloud platform. In order to validate the effectiveness of the proposed method, the IoT-based wave power generation condition monitoring system test platform is established. The experiment results illustrate the high efficiency and reliability of proposed method. The proposed method has a potential of practical applications.

关键词： wave power generation fault diagnosis wave power plants condition monitoring Internet of Things learning (artificial intelligence) power grids grid-connected wave power generation systems cloud platform IoT-based wave power generation condition monitoring system test platform compressed sensing method CS method extreme learning machine algorithm elm algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel On-line Alumina Concentration Measurement System 12

A Novel On-line Alumina Concentration Measurement System

引用

IEEE International Conference on Mechatronics & Automation

作者： Zhang, Sen Yang, Qiang Yin, Yixin Cao, Bin Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing Peoples R China Guiyang Aluminum Magnesium Design & Res Inst Guiyang Peoples R China

ISBN: (纸本)9781479970988

The concentration of alumina in the electrolyte is of great significance during the production of aluminum;it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on the voltage between the anode and the cathode, the current of the anode rod and the modified extreme learning machine for online measurement of the alumina concentration is proposed. In order to achieve the soft sensing scheme, considering the problems on the work spot, such as anode effect, the paper mainly develops a system that can realize the online measurement of the voltage between the anode and the cathode. The hardware of the system is composed of three parts including protection circuit, filter circuit and data acquisition card. When the anode effect occurs, the protection circuit which is used to ensure the safe use of the acquisition device will switch off the connection between the voltage and the data collection card. When the voltage returns to normal level, it will switch on the connection. The modified elm algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The experimental results show that the approach can give accurate estimations of alumina concentration within 6 percent relative error.

关键词： Alumina Concentration Aluminum electrolysis Anode current elm algorithm Voltage measurement

来源：评论

学校读者我要写书评

暂无评论

A Forecasting Method of Air Conditioning Energy Consumption Based on Extreme Learning Machine algorithm 6

A Forecasting Method of Air Conditioning Energy Consumption ...

引用

2017 IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS’17)

作者： Xu Yang Jingjing Gao Lei Zhang Xiaoli Li Liu Gu Jiarui Cui Chaonan Tong School of Automation and Electrical Engineering University of Science and Technology Beijing College of Electronic Information and Control Engineering Beijing University of Technology

ISBN: (纸本)9781509054626

This paper deals with the issue on air conditioning energy consumption and system monitoring of different data in building. Various environmental parameters inside the building are changed in real time, while the conventional air conditioning energy consumption forecasting with the load simulation software cannot adapt to these variations. Therefore, the air conditioning energy consumption forecasting model is established based on extreme learning machine(elm) algorithm, within the interior environmental parameters of the building. These parameters are obtained through the building monitoring system which takes into account the environmental parameters, number of people, region area and energy consumption. The performance and effectiveness of the proposed forecasting model of air conditioning energy consumption are demonstrated through a case study of a building from practical engineering.

关键词： Air Conditioning Energy Consumption Forecasting Model Building Monitoring System elm algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel Forecasting Method for Large-scale Sales Prediction Using Extreme Learning Machine 7

A Novel Forecasting Method for Large-scale Sales Prediction ...

引用

7th International Joint Conference on Computational Sciences and Optimization (CSO)

作者： Gao, Ming Xu, Wei Fu, Hongjiao Wang, Mingming Liang, Xun Renmin Univ China Sch Informat Beijing Peoples R China

ISBN: (纸本)9781479953721

With the rise of e-commerce business, sales forecasting plays an increasingly important role, for accurate and speedy forecasting can help e-commerce companies solve all the uncertainty associated with demand and supply and reduce inventory cost. As the rapid growth in the amount of data, traditional intelligence models like Neural Networks have weakness in terms of speed. In this paper, we introduce the algorithm of elm (extreme learning machine). In addition, we subjoin many e-commerce related indicators to increase the accuracy and reliability of prediction. In sum, the new model provides a better result both in terms of speed and accuracy. Experiments are conducted with the real sales data from an e-commerce company in China.

关键词： Sales prediction elm algorithm E-commerce

来源：评论

学校读者我要写书评

暂无评论

Prediction of Thalassemia Based on SAelm Hybrid algorithm 3

Prediction of Thalassemia Based on SAELM Hybrid Algorithm

引用

3rd International Conference on Data Science and Business Analytics (ICDSBA)

作者： Xu, Wenlin Song, Yaolian Zou, Tuanbiao Kunming Univ Sci & Technol Fac Informat Engn & Automat Kunming Yunnan Peoples R China Yunnan Maternal & Child Hlth Care Hosp Kunming Yunnan Peoples R China

ISBN: (纸本)9781728146447

Thalassemia is a serious hereditary disease, which cannot be cured. It's valuable to study on thalassemia. The input weights and biases of Extreme Learning Machine (elm) can be randomly initialized, which sometimes cannot get the better result. So a new algorithm named SAelm based on thalassemia is proposed by using the strong global optimization ability of Simulated Annealing (SA) algorithm, which can find the best weights and biases of elm algorithm. Simulation results illustrated that the SAelm is better than elm in the main evaluation indices, so SAelm algorithm can be used as a medical reference index in the screening of thalassemia.

关键词： elm algorithm Simulated Annealing algorithm SAelm algorithm Thalassemia

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：