Back to Search
Start Over
Linguistic assessment information risky multi-criteria decision-making about wind power investment
- Source :
- Journal of Intelligent & Fuzzy Systems. 30:3017-3023
- Publication Year :
- 2016
- Publisher :
- IOS Press, 2016.
-
Abstract
- In this paper, we give a risky decision-making approach based on prospect theory and cloud theory to solve the wind power investment problem. In this problem, the criteria value of alternative is linguistic assessment information and the criteria's weights are partially known. Firstly, we use the cloud theory to transfer the linguistic variables into one-dimensional normal cloud model. On the basis of defining the normal cloud model comparison rule and viewing all other alternatives as the reference point, a cloud prospect value function can be defined. Then, the cloud prospect decision-making matrix can be attained. Secondly, to get the optimal criteria weights, an optimization programming model which satisfies the algorithm of maximizing deviation and the decision makers' subjective information is enacted. After that, we aggregate the clouds of each alternative as a comprehensive cloud. Then the order of alternatives can be listed by comparing comprehensive cloud of each alternative. Finally, an illustrative example about wind power investment is given and we verify the effectiveness and feasibility of this approach which can be valuable in the wind power investment decision-making.
- Subjects :
- Statistics and Probability
Wind power
business.industry
Computer science
05 social sciences
Aggregate (data warehouse)
General Engineering
Cloud computing
02 engineering and technology
Investment (macroeconomics)
Linguistics
Artificial Intelligence
Prospect theory
Order (exchange)
Bellman equation
0502 economics and business
Value (economics)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
050207 economics
business
Astrophysics::Galaxy Astrophysics
Subjects
Details
- ISSN :
- 18758967 and 10641246
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Accession number :
- edsair.doi...........14ecb94aa7d7085a5a3da0f723c457a5