Permeability can be directly measured using cores taken from the reservoir in the laboratory. Due to high cost associated with coring, cores are available in a limited number of wells in a field. Many empirical models, statistical methods, and intelligent techniques were suggested to predict permeability in un-cored wells from easy-to-obtain and frequent data such as wireline logs. The main obj...

nonnegative matrix factorization (nmf) is a common method in data mining that have been used in different applications as a dimension reduction, classification or clustering method. methods in alternating least square (als) approach usually used to solve this non-convex minimization problem.  at each step of als algorithms two convex least square problems should be solved, which causes high com...

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

The evaluation and prediction of the failure probability and safety levels of composite components and structures is of extreme importance in structural design and manufacturing. A new application of data mining techniques for predicting the behavior of pin-loaded composite joints is presented. The proposed system consists of combining different data mining and soft computing techniques such as...

Cancer detection is one of the important research topics in medical science. In bioinformatics age, gene expression data can be used for the cancer detection. Data mining techniques, such as pattern association, classification and clustering, are now frequently applied in cancer and gene expressions correlation studies. Classification is very important among these techniques of data mining. Her...