| Title |
Big Data Based Intelligent Decision Support System for Sustainable Regional Development |
| ID_Doc |
65284 |
| Authors |
Zhou, H; Noble, C; Cotter, J |
| Title |
Big Data Based Intelligent Decision Support System for Sustainable Regional Development |
| Year |
2015 |
| Published |
|
| DOI |
10.1109/SmartCity.2015.169 |
| Abstract |
Timely intelligent decision making is increasingly important for modern society. With the availability of big data and advanced artificial intelligence in decision making, more objective and evidence-based quantitative smart decisions can be made in a timely manner. This research proposed a big data based intelligent decision support system (B-IDSS) for sustainable business development. The system can be used by both the government agencies and corporate business (e.g. farms. mining) in advanced planning, collaboration and management. This paper also addresses the performance optimization as bilevel decision-making problem with one leader and multiple followers. An extended Kuhn-Tucker approach is introduced as one of the algorithms that can be adapted in the system. |
| Author Keywords |
decision making; business model; sustainability; big data; bilevel programming |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000392313100133 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Theory & Methods; Green & Sustainable Science & Technology |
| Research Area |
Computer Science; Science & Technology - Other Topics |
| PDF |
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