The prediction of time series has been widely applied to many fields such as enrollments, stocks, weather and so on. In this paper, a new prediction method based on fuzzy cognitive map with information granules is proposed, in which fuzzy cmeans clustering algorithm is used to automatically abstract information granules and transform the original time series into granular time series, and subse...

Decision trees are commonly employed as data classifiers in various research fields, but also in real-world application domains. In the fuzzy neural framework, decision trees can offer valuable assistance in determining a proper initial system structure, which means not only feature selection, but also rule extraction and organization. This paper proposes a synergistic model that combines the a...

Intuitionistic fuzzy sets as proposed by Atanassov, have gained much attention from past and latter researchers for applications in various fields. Similarity measures between intuitionistic fuzzy sets were developed afterwards. However, it does not cater the conflicting behavior of each element evaluated. We therefore made some modification to the similarity measure of IFS by considering confl...

This article presents an agent-based fuzzy cognitive map (ABFCM) developed injecting the concept of multi-agent system (MAS) into the fuzzy cognitive map (FCM). Fuzzy cognitive map is used for qualitative modeling and simulation. Compared to the FCM, the ABFCM enables different inference algorithms in each node enabling simulation of systems with diverse behavior concepts. Each map node can exh...

The concept of controlling non-linear systems is one the significant fields in scientific researches for the purpose of which intelligent approaches can provide desirable applicability. Fuzzy systems are systems with ambiguous definition and fuzzy control is an especial type of non-linear control. Inverse pendulum system is one the most widely popular non-linear systems which is known for its s...

Fuzzy logic and Genetic Algorithm combination is becoming popular intelligent technique among researchers to investigate the decision making process in different application fields. This paper proposes a methodology of performance analysis of CRM systems based on such hybridization of fuzzy logic and genetic Algorithm. The technique is referred to as Genetic Fuzzimetric Technique. It is based o...

Knowledge in some fields like Medicine, Science and Engineering is very dynamic because of the continuous contributions of research and development. Therefore, it would be very useful to design knowledge-based systems capable to be adjusted like human cognition and thinking, according to knowledge dynamics. Aiming at this objective, a more generalized fuzzy Petri net model for expert systems is...

Combining multiple neural networks has been used to improve the decision accuracy in many application fields including pattern recognition and classification. In this paper, we investigate the potential of this approach for land cover change detection. In a first step, we perform many experiments in order to find the optimal individual networks in terms of architecture and training rule. In the...

Fuzzy inference systems have been applied in recent years in various medical fields due to their ability to obtain good results featuring white-box models. Adaptive Neuro-Fuzzy Inference System (ANFIS), which combines adaptive neural network capabilities with the fuzzy logic qualitative approach, has been previously used in modelling survival of breast cancer patients based on patient groups de...

This paper presents the COG-FPOM, a model based on the Fuzzy Pay-Off Method (FPOM). The FPOM is a scenario-based real option valuation method that uses fuzzy numbers as possibility distributions. The paper shows an unexpected result generated by the original FPOM, in which the real option would have a negative value. It further analyses its reasons and suggests a way to overcome it, by using th...