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A Role-dependent Data-driven Approach for High Density Crowd Behavior Modeling
Proceedings of the 2016 annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation - SIGSIM-PADS '16
◽
10.1145/2901378.2901382
◽
2016
◽
Cited By ~ 5
Author(s):
Mingbi Zhao
◽
Jinghui Zhong
◽
Wentong Cai
Keyword(s):
High Density
◽
Behavior Modeling
◽
Data Driven
◽
Dependent Data
◽
Crowd Behavior
◽
Data Driven Approach
Download Full-text
Related Documents
Cited By
References
A Role-Dependent Data-Driven Approach for High-Density Crowd Behavior Modeling
ACM Transactions on Modeling and Computer Simulation
◽
10.1145/3177776
◽
2018
◽
Vol 28
(4)
◽
pp. 1-25
◽
Cited By ~ 4
Author(s):
Mingbi Zhao
◽
Jinghui Zhong
◽
Wentong Cai
Keyword(s):
High Density
◽
Behavior Modeling
◽
Data Driven
◽
Dependent Data
◽
Crowd Behavior
◽
Data Driven Approach
Download Full-text
A data-driven approach to modeling high-density terminal areas: A scenario analysis of the new Beijing, China airspace
Chinese Journal of Aeronautics
◽
10.1016/j.cja.2016.12.030
◽
2017
◽
Vol 30
(2)
◽
pp. 538-553
◽
Cited By ~ 11
Author(s):
Max Z. Li
◽
Megan S. Ryerson
Keyword(s):
Scenario Analysis
◽
High Density
◽
Data Driven
◽
Data Driven Approach
◽
Beijing China
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A novel data-driven approach to tree species classification using high density multireturn airborne lidar data
Image and Signal Processing for Remote Sensing XXIV
◽
10.1117/12.2325634
◽
2018
◽
Author(s):
Aravind Harikumar
◽
Claudia Paris
◽
Francesca Bovolo
◽
Lorenzo Bruzzone
Keyword(s):
Tree Species
◽
High Density
◽
Airborne Lidar
◽
Data Driven
◽
Lidar Data
◽
Species Classification
◽
Tree Species Classification
◽
Data Driven Approach
◽
Airborne Lidar Data
Download Full-text
Data Driven Approach to Forecast Building Occupant Complaints
Construction Research Congress 2020
◽
10.1061/9780784482865.019
◽
2020
◽
Author(s):
Sena Assaf
◽
Mohamad Awada
◽
Issam Srour
Keyword(s):
Data Driven
◽
Data Driven Approach
Download Full-text
Analysis and Interpretation of Multi-Source Data at the Hydraulic Fracturing Test Site: A Data-Driven Approach to Improve Well Performance Evaluation in Heterogeneous Formations
Proceedings of the 2020 Latin America Unconventional Resources Technology Conference
◽
10.15530/urtec-2020-1560
◽
2020
◽
Author(s):
Shadi Salahshoor
Keyword(s):
Performance Evaluation
◽
Hydraulic Fracturing
◽
Test Site
◽
Data Driven
◽
Well Performance
◽
Source Data
◽
Data Driven Approach
◽
Heterogeneous Formations
Download Full-text
Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach
10.21236/ada572180
◽
2012
◽
Author(s):
Michael Ghil
◽
Mickael D. Chekroun
◽
Dmitri Kondrashov
◽
Michael K. Tippett
◽
Andrew Robertson
◽
...
Keyword(s):
Dynamic Models
◽
Data Driven
◽
Stochastic Dynamic
◽
Extended Range
◽
Data Driven Approach
◽
Low Dimensional
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Are Self-Reported Smoking Information As Good As Clinical Measures? Evidence From a Data Driven Approach
SSRN Electronic Journal
◽
10.2139/ssrn.3173307
◽
2018
◽
Author(s):
Benjamin Ukert
Keyword(s):
Data Driven
◽
Data Driven Approach
◽
Clinical Measures
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Head Motion Generation with Synthetic Speech: A Data Driven Approach
10.21437/interspeech.2016-419
◽
2016
◽
Cited By ~ 5
Author(s):
Najmeh Sadoughi
◽
Carlos Busso
Keyword(s):
Data Driven
◽
Synthetic Speech
◽
Head Motion
◽
Motion Generation
◽
Data Driven Approach
Download Full-text
A Mostly Data-Driven Approach to Inverse Text Normalization
10.21437/interspeech.2017-1274
◽
2017
◽
Cited By ~ 1
Author(s):
Ernest Pusateri
◽
Bharat Ram Ambati
◽
Elizabeth Brooks
◽
Ondrej Platek
◽
Donald McAllaster
◽
...
Keyword(s):
Data Driven
◽
Data Driven Approach
◽
Text Normalization
Download Full-text
Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment
Sensors
◽
10.3390/s18051571
◽
2018
◽
Vol 18
(5)
◽
pp. 1571
◽
Cited By ~ 4
Author(s):
Jhonatan Camacho Navarro
◽
Magda Ruiz
◽
Rodolfo Villamizar
◽
Luis Mujica
◽
Jabid Quiroga
Keyword(s):
Correlation Analysis
◽
Damage Assessment
◽
Structural Damage
◽
Cross Correlation
◽
Data Driven
◽
Cross Correlation Analysis
◽
Data Driven Approach
Download Full-text
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