Applications of Fuzzy Ensemble Approaches in Modeling, Forecasting, and Control
1Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan
2Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan
3TEC de Monterrey, Campus Ciudad de México, RZMCM, México, DF, Mexico
4MIE Department, Louisiana State University, Baton Rouge, LA, USA
Applications of Fuzzy Ensemble Approaches in Modeling, Forecasting, and Control
Description
Fuzzy systems have been successfully applied to various fields. However, most applications are based on a single fuzzy system. The simultaneous use of multiple fuzzy systems may be able to achieve better results. In addition, seeing a problem from various perspectives ensures that no parts are ignored when solving the problem. Based on these points of view, the ensemble of fuzzy systems has great potential for the modeling, forecasting, and control of complex systems under an uncertain, restricted, or subjective environment.
In the limited literature, fuzzy ensemble approaches have been successfully applied to group decision-making, collaborative forecasting, collective intelligence, population-driven optimization, distributed clustering, multiperspective design, and others. However, it is expected that new applications of fuzzy ensemble approaches in other fields will be developed.
This special issue is intended to provide the details of developing fuzzy ensemble approaches and their applications. It features a balance between the state-of-the-art research and the usually reported applications. This special issue also provides a forum for researchers and practitioners to review and disseminate quality research work on fuzzy ensemble approaches and their applications in modeling, forecasting, and control and to identify critical issues for further developments. Potential topics include, but are not limited to:
- Mamdani’s fuzzy systems and ensembles
- TSK fuzzy systems and ensembles
- Neural fuzzy ensembles, fuzzy ensemble of artificial neural networks
- Fuzzy artificial bee colony (ABC)
- Fuzzy ensemble classifier/clustering
- Fuzzy ensemble forecasting
- Fuzzy particle swarm optimization (PSO)
- Fuzzy collaborative systems
- Fuzzy agent systems
- Linguistic variable-based fuzzy ensemble approaches
- Fuzzy-rough classifier ensemble
- Evolving ensemble of fuzzy models
- Fuzzy cognitive map ensemble
- Communication protocol
- Quality of collaboration
- Aggregation
- Stability of fuzzy ensemble
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