This work focuses on the formalization of a Fuzzy Cognitive Map based decision support system using fuzzy If-Then rules (extracted from data) accompanied with the available experts’ knowledge. The proposed approach is applied to build a Fuzzy Cognitive Map (FCM) grading tool, an advanced FCM-based model used for prediction. The FCM is a modeling methodology based on exploiting knowledge and exp...

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new m...

Introduction Knowledge management (KM) and artificial intelligence (AI) are interconnected disciplines to discern information for information management systems. Researchers have raised issues of knowledge that are living and active. Decisions based on real life knowledge bases are subjective judgments in nature. AI has well-developed cognitive tools that can process qualitative information of ...

Haze-fog has seriously hindered the sustainable development of the ecological environment and caused great harm to the physical and mental health of residents in China. Therefore, it is important to probe the formation of haze-fog for its early warning and prevention. The formation of haze-fog is, in fact, a fuzzy nonlinear process. The formation of haze-fog is such a complex process that it is...

A fuzzy cognitive maps (FCM) is a cognitive map within the relations between the elements. FCM has been widely used in many applications such as experts system and knowledge engineering. However, classical FCM is inherently short of sufficient capability of representing and aggregating uncertain information. In this paper, generalized FCM (GFCM) is proposed based on genetic algorithm and interv...

Fuzzy cognitive map (FCM) is a universal tool for modeling dynamic decision support systems. It can be constructed by the experts or learned based on data. FCM models learned from data are denser than those created by experts. We developed an evolutionary learning approach for fuzzy cognitive maps based on density and system performance indicators. It allows to select only the most significant ...

Fuzzy Cognitive Maps (FCMs) is a causal graph, which shows the relations between essential components in complex systems. Experts who are familiar with the system components and their relations can generate a related FCM. There is a big gap when human experts cannot produce FCM or even there is no expert to produce the related FCM. Therefore, a new mechanism must be used to bridge this gap. In ...

This paper proposes a new methodology for designing Fuzzy Cognitive Maps using crisp decision trees that have been fuzzified. Fuzzy cognitive map is a knowledge-based technique that works as an artificial cognitive network inheriting the main aspects of cognitive maps and artificial neural networks. Decision trees, in the other hand, are well known intelligent techniques that extract rules from...

Part III is concluded with this chapter that proposes a Fuzzy Cognitive Map (FCM)-based modeling of the Quality of Interaction (QoI) of the Learning Management System (LMS) users within a blended (b)learning context, namely FCM-QoI model. Two training/testing scenarios were conducted and explored here, i.e., time-dependent and time-independent, using as pre-validated QoI data the ones presented...

A wide variety of knowledge acquisition methods exist for conventional knowledge types such as production rule, semantic knowledge, etc. However, need for causal knowledge acquisition has not been stressed in the expert systems fields. The objectives of this paper are to (1) suggest a causal knowledge acquisition process and (2) investigate the causal knowledge-based inference process. FCM (Fuz...