scholarly journals Multi-level information fusion for learning a blood pressure predictive model using sensor data

2020 ◽  
Vol 58 ◽  
pp. 24-39 ◽  
Author(s):  
Monika Simjanoska ◽  
Stefan Kochev ◽  
Jovan Tanevski ◽  
Ana Madevska Bogdanova ◽  
Gregor Papa ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Predictive Model ◽  
Information Fusion ◽  
Sensor Data ◽  
Level Information ◽  
Multi Level

Application of multi-level information fusion for wear particle recognition of ferrographic images

2018 ◽  
Vol 26 (6) ◽  
pp. 1551-1560
Author(s):  
徐 斌 XU Bin ◽  
温广瑞 WEN Guang-rui ◽  
苏 宇 SU Yu ◽  
张志芬 ZHANG Zhi-fen ◽  
陈 峰 CHEN Feng ◽  
...  
Keyword(s):  
Information Fusion ◽  
Wear Particle ◽  
Particle Recognition ◽  
Level Information ◽  
Multi Level

Multi-level information fusion to alleviate network congestion

2020 ◽  
Vol 63 ◽  
pp. 248-255 ◽  
Author(s):  
Joel Weijia Lai ◽  
Jie Chang ◽  
L. K. Ang ◽  
Kang Hao Cheong
Keyword(s):  
Information Fusion ◽  
Network Congestion ◽  
Level Information ◽  
Multi Level

Multi-level information fusion for spatiotemporal monitoring in water distribution networks

2015 ◽  
Vol 42 (7) ◽  
pp. 3813-3831 ◽  
Author(s):  
Farzad Aminravan ◽  
Rehan Sadiq ◽  
Mina Hoorfar ◽  
Manuel J. Rodriguez ◽  
Homayoun Najjaran
Keyword(s):  
Information Fusion ◽  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Level Information ◽  
Multi Level

Topic identification of text‐based expert stock comments using multi‐level information fusion

2020 ◽  
Author(s):  
Feng Zhao ◽  
Jiahui Zhang ◽  
Zhiyuan Chen ◽  
Xiaofeng Zhang ◽  
Qingsong Xie
Keyword(s):  
Information Fusion ◽  
Topic Identification ◽  
Level Information ◽  
Multi Level

Distributed Information Fusion Structure Based on Data Fusion Tree

2011 ◽  
Vol 225-226 ◽  
pp. 488-491
Author(s):  
Ying Hua Xue ◽  
Jing Li
Keyword(s):  
Data Fusion ◽  
Information Fusion ◽  
Search Efficiency ◽  
Precise Localization ◽  
Distributed Information ◽  
Traditional Mode ◽  
Level Information ◽  
Multi Level ◽  
Different Levels ◽  
Better Than

A distributed information fusion structure based on data fusion tree is built to realize precise localization and efficient navigation for the mobile robot. The multi-class, multi-level information from robot and environment is fused using different algorithms in different levels, and make the robot have a deeper understanding to the whole environment. Experiments demonstrate that the new model proposed in the paper can improve the positioning precision of robot greatly, and the search efficiency and success rate are also better than traditional mode.

Distributed Monitoring and Intelligent Fault Diagnosis System for Large-Scale Electro-Hydraulic Devices

2015 ◽  
Vol 779 ◽  
pp. 163-168
Author(s):  
Gui You Hao ◽  
Jie Cheng ◽  
Zong Gui Zheng ◽  
Zhi Gang Yu ◽  
Gang Wu
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Large Scale ◽  
Sensor Data ◽  
Distributed Monitoring ◽  
Diagnosis System ◽  
Fusion Methods ◽  
Level Information ◽  
Fault Diagnosis System ◽  
Hydraulic Devices

In this paper, a distributed monitoring and intelligent diagnosis system is designed for large-scale electro-hydraulic devices, based on the utilization of information fusion technology. As a result of using multi-sensor data level, feature level and decision-making level information fusion methods, both precision and real-time performance of condition monitoring and fault diagnosis have been greatly improved, which leads to an advance in the accuracy of monitoring and diagnosis.

Sign in / Sign up

Export Citation Format

Share Document