Ladar Data Filtering Method Based on Improved Progressive Multi-Scale Mathematic Morphology

2013 ◽  
Vol 33 (3) ◽  
pp. 0328001
Author(s):  
赵明波 Zhao Mingbo ◽  
何峻 He Jun ◽  
田军生 Tian Junsheng ◽  
付强 Fu Qiang
Keyword(s):  
Data Filtering ◽  
Filtering Method ◽  
Multi Scale ◽  
Mathematic Morphology

Falsified data filtering method for smart grid wireless communication based on SVM

2020 ◽  
Vol 13 (4) ◽  
pp. 177
Author(s):  
Fen Liu ◽  
Zheng Yu ◽  
Yixi Wang ◽  
Hao Feng ◽  
Zhiyong Zha ◽  
...  
Keyword(s):  
Wireless Communication ◽  
Smart Grid ◽  
Data Filtering ◽  
Filtering Method

scholarly journals An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

2016 ◽  
Vol 8 (6) ◽  
pp. 501 ◽  
Author(s):  
Wuming Zhang ◽  
Jianbo Qi ◽  
Peng Wan ◽  
Hongtao Wang ◽  
Donghui Xie ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Data Filtering ◽  
Cloth Simulation ◽  
Filtering Method ◽  
Airborne Lidar Data

scholarly journals Using Data on Bike-Sharing System User Stopovers in Smart Tourism: A Case Study

2021 ◽  
Vol 23 (2) ◽  
pp. G1-G12
Author(s):  
Krystian Banet
Keyword(s):  
Smart Cities ◽  
Public Spaces ◽  
Data Filtering ◽  
Analysis And Design ◽  
Filtering Method ◽  
Bike Sharing ◽  
System User ◽  
Using Data ◽  
Smart Tourism

Bike-sharing systems are an important element in development of the smart cities and datasets from these systems are one of the ways to obtain large amount of information on bicycle traffic. These usually contain data on the origin and destination of each trip, as well as its time and duration. Alongside the basic data, some operators also provide information on the exact route picked by each user. This allows researchers to study stopovers, which may serve as a source of interesting information on human behaviour in public spaces and, as a consequence, help improve its analysis and design. However, using the raw data may lead to important errors because most stops occur in the vicinity of bike stations or are related to traffic problems, as evidenced by the case study of Cracow. The data filtering method proposed below opens up the possibility for using such datasets for further research on bike user behaviour and public spaces.

Dynamic Filtering Method for GPS Based on Multi-Scale

2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Wen An ◽  
Youming Liu ◽  
Guowei Wang ◽  
Zhiyong Liu ◽  
Tingjun Li
Keyword(s):  
Filtering Method ◽  
Multi Scale ◽  
Dynamic Filtering
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