Clustering algorithms are commonly used in the mining of static data. Some examples include data for relationships between variables and segmentation into components. The use a clustering algorithm real-time is much less common. This due to variety factors, including algorithm’s high computation cost. In other words, may be impractical or near-real-time implementation. Furthermore, necessitate ...

Three Neuro-Fuzzy Inference Systems (ANFIS) including Grid Partitioning (GP), Subtractive Clustering (SCM) and Fuzzy C-means clustering Methods (FCM) have been used to predict the groutability of granular soil samples with cement-based grouts. Laboratory data from related available in litterature was used for the tests. Several parameters were taken into account in the proposed models: water:ce...

Clustering is a key data mining problem. Densitybased clustering algorithms have recently gained popularity in the data mining field. Density and grid based technique is a popular way to mine clusters in a large spatial datasets wherein clusters are regarded as dense regions than their surroundings. The attribute values and ranges of these attributes characterize the clusters In this paper we a...

background: the two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. the objective of the present study was to classify the different countries based on the death rates from sex specific cancers. methods : in this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide repo...