Fuzzy cognitive maps (FCMs) keep growing in popularity within the scientific community.
However, despite substantial advances in the theory and applications of FCMs, there is a …

This survey makes a review of the most recent applications and trends on fuzzy cognitive
maps (FCMs) over the past decade. FCMs are inference networks, using cyclic digraphs, for …

Abstract Fuzzy Cognitive Map (FCM) modelling is highly suitable for the demands of future
studies: it uses a mix of qualitative and quantitative approaches, it enables the inclusion of …

This study presents a survey on the most recent learning approaches and algorithms that
are related to fuzzy cognitive maps (FCMs). FCMs are cognition fuzzy influence graphs …

The main drawback of the Story-and-Simulation approach is the weak link between
qualitative and quantitative scenarios. A semi-quantitative tool, Fuzzy Cognitive Map**, is …

Several energy transition plans attempt to establish low-carbon practices towards a circular
bio-economy in order to reduce greenhouse gas emissions. However, most actions only try …

Fuzzy cognitive maps (FCM) are graph-based modeling tools. FCM can to be used for
structuring and supporting decisional processes. Also, FCM allow develo** what-if …

To maintain the vibrations of the gyroscope proof mass, a trajectory tracking control system
using a neural network estimator is proposed. The proposed control system incorporates a …

This study presents an integrated genetic algorithm (GA) and artificial neural network (ANN)
to estimate and predict electricity demand using stochastic procedures. The economic …

Background and Objective A high percentage of medical errors, committed because of
physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to …