Fuzzy cognitive maps have received increasing attention for the representation of causal knowledge, being especially useful in biomedicine. Recently some extension for using fuzzy cognitive maps using the paradigm of computing with words in order to provide causal models that are easily understood have been proposed. Nevertheless, there are situations in which experts hesitate between several values to assess the causal relation. To this end, we propose the use of of hesitant fuzzy linguistic term sets. Finally, the paper presents an illustrative example of the model for biomedical knowledge representation.
Fuzzy cognitive maps have received increasing attention for the representation of the causal knowledge especially useful in knowledge management. This paper proposes a model CRM critical success factor modelling and analysis based on fuzzy cognitive maps and using the paradigm of Computing with Words, in order to provide causal models easy to understand. To this end, the use of linguistic representation model based on linguistic 2-tuple in the competitive fuzzy cognitive maps is proposed, which allowing to perform the Computing with Words Processes without losing information. The main advantage of the model proposed for is that it allows increasing the interpretability of the causal models, being this fact knowledge management. Last, the paper presents a case study of the model proposed, as well as recommendations for future works.
A key goal of any engineering and software engineering in particular, is the quality of the final product. Software quality is often determined by the ability to meet the needs of customers and end users, as obtained as software requirements. To satisfy that needs is important a correct requirement engineering process in general, and a correct requirement prioritization in particular. Prioritizing software requirements is a complex decision making process. Traditional approaches do not perform aggregation of criteria with sufficient flexibility and adaptability to the specific contexts of organizations. In this paper we propose a requirements prioritization method that uses hierarchical aggregation process for information fusion. The proposal allows the inclusion of aspects such as the importance of the criteria and simultaneity. To demonstrate the applicability of the proposal a case study is developed. The paper ends with further work recommendations for extending the method.
Show abstract
Full Text
