Research on the Uncertainty Decision Model of the Regional Collaborative Innovation System Based on an Improved Ant Colony Algorithm
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-15
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The regional collaborative innovation system is a nonlinear complex system, which has obvious uncertainty characteristics in the aspects of member selection and evolution.
Ant colony algorithm, which can do the uncertainty collaborative optimization decision-making, is an effective tool to solve the uncertainty decision path selection problem.
It can improve the cooperation efficiency of each subsystem and achieve the goal of effective cooperation.
By analysing the collaborative evolution mechanisms of the regional innovation system, an evaluation index system for the regional collaborative innovation system is established considering the uncertainty of collaborative systems.
The collaborative uncertainty decision model is constructed to determine the regional innovation system’s collaborative innovation effectiveness.
The improved ant colony algorithm with the pheromone evaporation model is applied to traversal optimization to identify the optimal solution of the regional collaborative innovation system.
The collaboration capabilities of the ant colony include pheromone diffusion so that local updates are more flexible and the result is more rational.
Finally, the method is applied to the regional collaborative innovation system.
American Psychological Association (APA)
Zhang, Xiaona& Wang, Fayin. 2016. Research on the Uncertainty Decision Model of the Regional Collaborative Innovation System Based on an Improved Ant Colony Algorithm. Scientific Programming،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1118166
Modern Language Association (MLA)
Zhang, Xiaona& Wang, Fayin. Research on the Uncertainty Decision Model of the Regional Collaborative Innovation System Based on an Improved Ant Colony Algorithm. Scientific Programming No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1118166
American Medical Association (AMA)
Zhang, Xiaona& Wang, Fayin. Research on the Uncertainty Decision Model of the Regional Collaborative Innovation System Based on an Improved Ant Colony Algorithm. Scientific Programming. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1118166
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118166