In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determin...

Fuzzy c-means (FCM) clustering is based on minimizing the fuzzy within cluster scatter matrix trace but FCM neglects the between cluster scatter matrix trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches import...

The weighting exponentm is called the fuzzifier that can influence the performance of fuzzy c-means (FCM). It is generally suggested that mA[1.5,2.5]. On the basis of a robust analysis of FCM, a new guideline for selecting the parameter m is proposed. We will show that a large m value will make FCM more robust to noise and outliers. However, considerably large m values that are greater than the...

The strategy of organizational lean production emphasizes on increasing efficiency, quality improvement and cycle time reduction by eliminating non-value added activities (MUDA). This paper presents a comprehensive approach based on data envelopment analysis (DEA), fuzzy DEA (FDEA), fuzzy cognitive map (FCM), Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Hierarchy Proce...

We propose a novel method F2C that can process the only information available in the early stages of a young high-technology venture: linguistic expert knowledge. This knowledge is the basis for the determination of an appropriate discount rate for the valuation of high-technology ventures in early stages of venture capital investments. A specific tool named Fuzzy Cognitive Map (FCM) is used th...

Recently, Fuzzy Grey Cognitive Maps (FGCM) has been proposed as a FCM extension. It is based on Grey System Theory, that it has become a very effective theory for solving problems within environments with high uncertainty, under discrete small and incomplete data sets. The proposed approach of learning FGCMs applies the Nonlinear Hebbian based algorithm determine the success of radiation therap...

A new approach for the construction of Fuzzy Cognitive Maps augmented by knowledge through fuzzy rule-extraction methods for medical decision making is investigated. This new approach develops an augmented Fuzzy Cognitive Mapping based Decision Support System combining knowledge from experts and knowledge from data in the form of fuzzy rules generated from rule-based knowledge discovery methods...

events contributes to the increasing challenges in political decision making, especially the decision to strengthen bilateral economic relationships between friendly nations. Obviously this becomes one of the critical decisions. Typically, such decisions are influenced by certain factors and variables that are based on heterogeneous and vague information. A serious problem that the decision mak...

Sports persons’ performance evaluation is a critical issue. The parameters used for this purpose are vague and imprecise. We propose a fuzzy cognitive map based cricket player performance evaluator tool that uses fuzzy logic to perform computation keeping in view the relations among various input parameters. A very simple and effective graphical user interface is build to use the proposed model...