Implementation of computing with words in evaluating training program
The decision-making problems have attracted the attention of many researchers in a wide range of disciplines. The decision situations in which multiple individuals involved, each with their own knowledge about alternatives of the decision problem requires advanced to deal with this difficulty techni...
- Autores:
-
Felix-Benjamín, Gerardo
Calero-Muela, Claudia
Esquivel, Renier
Bello-Pérez, Rafael
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60642
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60642
http://bdigital.unal.edu.co/58974/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Computing with words
group decision making
decision analysis
impact of training.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | The decision-making problems have attracted the attention of many researchers in a wide range of disciplines. The decision situations in which multiple individuals involved, each with their own knowledge about alternatives of the decision problem requires advanced to deal with this difficulty techniques. This work evaluates the impact of training received by a group of workers in the assessments are modeled using different kinds of information provided by different groups of experts to manage the uncertainty and subjectivity of such assessments for there to infer its relationship with the training received. Therefore, it is necessary and appropriate to establish a framework adapted to the heterogeneous nature of these criteria. Model and manage uncertainty has been successful and involves making computing processes with words hence the model 2-tuples linguistic representation is offered as a solution for their accuracy, ease of information management in complex frameworks, as to give greater interpretability of the resulting data. |
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