| Title |
Big data analytics: Computational intelligence techniques and application areas |
| ID_Doc |
40136 |
| Authors |
Iqbal, R; Doctor, F; More, B; Mahmud, S; Yousuf, U |
| Title |
Big data analytics: Computational intelligence techniques and application areas |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.techfore.2018.03.024 |
| Abstract |
Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment. |
| Author Keywords |
Smart city; Big data; Big data analytics; Computational intelligence; CI applications |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:000527366500004 |
| WoS Category |
Business; Regional & Urban Planning |
| Research Area |
Business & Economics; Public Administration |
| PDF |
https://pureportal.coventry.ac.uk/files/23233843/Binder2.pdf
|