According to the fundamental goal of remote sensing technology, the image classification of desired sensors can be introduced as the most important part of satellite image interpretation. There exist various algorithms in relation to the supervised land use classification that the most pertinent one should be determined. Therefore, this study has been conducted to determine the best and most su...

Today, a great deal of data is generated in the medical field. Acquiring useful knowledge from this raw data requires data processing and detection of meaningful patterns and this objective can be achieved through data mining. Using data mining to diagnose and prognose heart diseases has become one of the areas of interest for researchers in recent years. In this study, the literature on the ap...

classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. in this article we have presented an appropriate model to classify customers who use internet banking service. the model is deve...

The objective of this research was to determine the best model and compare performances in terms of producing landuse maps from six supervised classification algorithms. As a result, different algorithms such as the minimum distance ofmean (MDM), Mahalanobis distance (MD), maximum likelihood (ML), artificial neural network (ANN), spectral anglemapper (SAM), and support vector machine (SVM) were...

Manual fingerprint classification algorithms are very time consuming, and usually not accurate. Fast and accurate fingerprint classification is essential to each AFIS (Automatic Fingerprint Identification System). This paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. A new structural algorit...