-
Previous Article
Analyzing opinion dynamics in online social networks
- BDIA Home
- This Issue
- Next Article
ADERSIM-IBM partnership in big data
1. | Disaster & Emergency Management, York University, Toronto, Ontario, M3J 1P3, Canada |
2. | Department of Mathematics and Statistics, York University, Toronto, Ontario, M3J 1P3, Canada |
This short notes announces the recent development of the Advanced Disaster, Emergency and Rapid Response Simulation Initiative, in collaboration with IBM-Canada. Focus is on the Big Data analytics techniques and the IBM's Intelligent Operations Centre for Emergency Management platform.
References:
[1] |
N. Y. Armonk,
As Hurricane Season Approaches, IBM and The Weather Company Collaborate on Emergency Management for Cities, New IBM Intelligent Operations Center for Emergency Management Uses Real-time Weather Data to Help Communities Predict and Prepare for Disasters, 2015. Available from: http://www-03.ibm.com/press/us/en/pressrelease/47160.wss. |
[2] |
J. Huang, A. Asgary and J. Wu,
Advanced disaster, emergency and rapid response simulation (ADERSIM), Big Data and Information Analytics, 1 (2016), v-v.
doi: 10.3934/bdia.2016.1.1v. |
[3] |
A. Amaye, K. Neville, and A. Pope, BigPromises: using organisational mindfulness to integrate big data in emergency management decision making, Journal of Decision Systems, 25 (2016), ISS. SUPl. |
[4] |
Operational insight helps city leaders manage a safer, smarter city, Intelligent Operations Center for Smarter Cities, 2016. Available from: http://www-03.ibm.com/software/products/en/intelligent-operations-center. |
show all references
References:
[1] |
N. Y. Armonk,
As Hurricane Season Approaches, IBM and The Weather Company Collaborate on Emergency Management for Cities, New IBM Intelligent Operations Center for Emergency Management Uses Real-time Weather Data to Help Communities Predict and Prepare for Disasters, 2015. Available from: http://www-03.ibm.com/press/us/en/pressrelease/47160.wss. |
[2] |
J. Huang, A. Asgary and J. Wu,
Advanced disaster, emergency and rapid response simulation (ADERSIM), Big Data and Information Analytics, 1 (2016), v-v.
doi: 10.3934/bdia.2016.1.1v. |
[3] |
A. Amaye, K. Neville, and A. Pope, BigPromises: using organisational mindfulness to integrate big data in emergency management decision making, Journal of Decision Systems, 25 (2016), ISS. SUPl. |
[4] |
Operational insight helps city leaders manage a safer, smarter city, Intelligent Operations Center for Smarter Cities, 2016. Available from: http://www-03.ibm.com/software/products/en/intelligent-operations-center. |
[1] |
Jimmy Huang, Ali Asgary, Jianhong Wu. Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM). Big Data & Information Analytics, 2016, 1 (1) : v-v. doi: 10.3934/bdia.2016.1.1v |
[2] |
Sarah Ibri. An efficient distributed optimization and coordination protocol: Application to the emergency vehicle management. Journal of Industrial and Management Optimization, 2015, 11 (1) : 41-63. doi: 10.3934/jimo.2015.11.41 |
[3] |
Rodrigo A. Garrido, Ivan Aguirre. Emergency logistics for disaster management under spatio-temporal demand correlation: The earthquakes case. Journal of Industrial and Management Optimization, 2020, 16 (5) : 2369-2387. doi: 10.3934/jimo.2019058 |
[4] |
Huai-Che Hong, Bertrand M. T. Lin. A note on network repair crew scheduling and routing for emergency relief distribution problem. Journal of Industrial and Management Optimization, 2019, 15 (4) : 1729-1731. doi: 10.3934/jimo.2018119 |
[5] |
Junyuan Lin, Timothy A. Lucas. A particle swarm optimization model of emergency airplane evacuations with emotion. Networks and Heterogeneous Media, 2015, 10 (3) : 631-646. doi: 10.3934/nhm.2015.10.631 |
[6] |
Nick Cercone, F'IEEE. What's the big deal about big data?. Big Data & Information Analytics, 2016, 1 (1) : 31-79. doi: 10.3934/bdia.2016.1.31 |
[7] |
Richard Boire. Understanding AI in a world of big data. Big Data & Information Analytics, 2018 doi: 10.3934/bdia.2018001 |
[8] |
Fan Zhang, Guifa Teng, Mengmeng Gao, Shuai Zhang, Jingjing Zhang. Multi-machine and multi-task emergency allocation algorithm based on precedence rules. Discrete and Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1501-1513. doi: 10.3934/dcdss.2019103 |
[9] |
Cristina Anton, Jian Deng, Yau Shu Wong, Yile Zhang, Weiping Zhang, Stephan Gabos, Dorothy Yu Huang, Can Jin. Modeling and simulation for toxicity assessment. Mathematical Biosciences & Engineering, 2017, 14 (3) : 581-606. doi: 10.3934/mbe.2017034 |
[10] |
Fanwen Meng, Kiok Liang Teow, Kelvin Wee Sheng Teo, Chee Kheong Ooi, Seow Yian Tay. Predicting 72-hour reattendance in emergency departments using discriminant analysis via mixed integer programming with electronic medical records. Journal of Industrial and Management Optimization, 2019, 15 (2) : 947-962. doi: 10.3934/jimo.2018079 |
[11] |
Pankaj Sharma, David Baglee, Jaime Campos, Erkki Jantunen. Big data collection and analysis for manufacturing organisations. Big Data & Information Analytics, 2017, 2 (2) : 127-139. doi: 10.3934/bdia.2017002 |
[12] |
Enrico Capobianco. Born to be big: Data, graphs, and their entangled complexity. Big Data & Information Analytics, 2016, 1 (2&3) : 163-169. doi: 10.3934/bdia.2016002 |
[13] |
Alacia M. Voth, John G. Alford, Edward W. Swim. Mathematical modeling of continuous and intermittent androgen suppression for the treatment of advanced prostate cancer. Mathematical Biosciences & Engineering, 2017, 14 (3) : 777-804. doi: 10.3934/mbe.2017043 |
[14] |
Alexandre Bayen, Rinaldo M. Colombo, Paola Goatin, Benedetto Piccoli. Traffic modeling and management: Trends and perspectives. Discrete and Continuous Dynamical Systems - S, 2014, 7 (3) : i-ii. doi: 10.3934/dcdss.2014.7.3i |
[15] |
Weidong Bao, Wenhua Xiao, Haoran Ji, Chao Chen, Xiaomin Zhu, Jianhong Wu. Towards big data processing in clouds: An online cost-minimization approach. Big Data & Information Analytics, 2016, 1 (1) : 15-29. doi: 10.3934/bdia.2016.1.15 |
[16] |
Yang Yu. Introduction: Special issue on computational intelligence methods for big data and information analytics. Big Data & Information Analytics, 2017, 2 (1) : i-ii. doi: 10.3934/bdia.201701i |
[17] |
Xiangmin Zhang. User perceived learning from interactive searching on big medical literature data. Big Data & Information Analytics, 2018 doi: 10.3934/bdia.2017019 |
[18] |
Yaguang Huangfu, Guanqing Liang, Jiannong Cao. MatrixMap: Programming abstraction and implementation of matrix computation for big data analytics. Big Data & Information Analytics, 2016, 1 (4) : 349-376. doi: 10.3934/bdia.2016015 |
[19] |
Shuhua Zhang, Xinyu Wang, Hua Li. Modeling and computation of water management by real options. Journal of Industrial and Management Optimization, 2018, 14 (1) : 81-103. doi: 10.3934/jimo.2017038 |
[20] |
Linhao Xu, Marya Claire Zdechlik, Melissa C. Smith, Min B. Rayamajhi, Don L. DeAngelis, Bo Zhang. Simulation of post-hurricane impact on invasive species with biological control management. Discrete and Continuous Dynamical Systems, 2020, 40 (6) : 4059-4071. doi: 10.3934/dcds.2020038 |
Impact Factor:
Tools
Metrics
Other articles
by authors
[Back to Top]