This paper aims at studying at length the various reasons for miracles with incidents from the Holy Bible adopting the Neutrosophic Cognitive Maps , a generalization of Fuzzy Cognitive Maps. The content gives preliminaries of FCM and NCM with a descriptive account of the problem and the various miracles witnessed in the Bible using NCM. The data acquired is collated to conclude on the most esse...

This paper presents a comparison of the three fuzzy based image segmentation methods namely Fuzzy C-Means (FCM), TYPE-II Fuzzy C-Means (T2FCM), and Intuitionistic Fuzzy C-Means (IFCM) for digital images with varied levels of noise. Apart from qualitative performance, the paper also presents quantitative analysis of these three algorithms using four validity functions-Partition coefficient (Vpc)...

Fuzzy Cognitive Maps (FCMs) are considered a soft computing technique combining elements of fuzzy logic and recurrent neural networks. They found multiple application in such domains as modeling system behavior, prediction time series, decision making process control. Less attention, however, has been turned towards using them pattern classification. In this work we propose an FCM based classif...

A social Semantic Web empowers its users to have access to col-­‐ lective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehi-­‐ cle BLOCKIN

Classical fuzzy C -means (FCM) clustering is performed in the input space, given the desired number of clusters. Although it has proven effective for spherical data, it fails when the data structure of input patterns is non-spherical and complex. In this paper, we present a novel kernel-based fuzzy C-means clustering algorithm (KFCM). Its basic idea is to transform implicitly the input data int...

Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly nonlinear system. Even though applications of FCM risk analysis presented various engineering fields, this research aims at modeling road based on macroscopic characteristics through FCM. ...

This paper elaborates on the application of Fuzzy Cognitive Maps (FCMs) in strategy maps (SMs). The limitations of the Balanced Scorecards (BSCs) and SMs are first discussed and analyzed. The need for simulated scenario based SMs is discussed and the use of FCMs as one of the best alternatives is presented. A software tool for the development, simulation and analysis of FCM based SMs is also pr...

Geological studies are very important at different steps of mining activities. Different uncertain geological criteria and factors show a significant impact during the underground operations mineral extraction process. The current study reports on evaluation classification coal seams for methane drainage-ability (MDA) through fuzzy hybrid approach. This problem was investigated due to importanc...

A conventional fuzzy cmeans (FCM) clustering algorithm did not use the spatial information of the data and is very much sensitive to noise. To improve the noise sensitivity of FCM, Spatial FCM (SFCM) incorporates the spatial information to improve the results. Intuitionistic fuzzy sets introduce hesitation factor in the fuzzy sets to enhance the performance of fuzzy sets and also added entropy ...