A software tool for FCM aggregation employing credibility weights and learning OWA operators

In this study, we present the functionalities of a new tool for FCMs using credibility weights and OWA-based operators for aggregation tasks. The average aggregation method for weighted interconnections among concepts is the most used method in FCM modeling. The aim of this research work is to (i) propose an alternative aggregation method based on learning OWA operators in aggregating FCM weights, assigned by many experts and/or stakeholders and (ii) to estimate and rank the experts’ credibility using a distance-based method. The applicability and usefulness of the proposed methodology in modeling and decision-making is demonstrated using poverty eradication strategies under DAY-NRLM (Deendayal Antyodaya Yojana-National Rural Livelihoods Mission) of India. The results produced by the proposed learning OWA operators are compared with the known average aggregation method of FCMs. These results imply that the proposed alternative FCM aggregation approach is really challenging when a large number of experts and stakeholders are engaged to design the overall FCM model.