klinkenberg permeability is an important parameter in tight gas reservoirs. there are conventional methods for determining it, but these methods depend on core permeability. cores are few in number, but well logs are usually accessible for all wells and provide continuous information. in this regard, regression methods have been used to achieve reliable relations between log readings and klinke...

the aim of this work is to examine the feasibilities of the support vector machines (svms) and k-nearest neighbor (k-nn) classifier methods for the classification of an aquifer in the khuzestan province, iran. for this purpose, 17 groundwater quality variables including ec, tds, turbidity, ph, total hardness, ca, mg, total alkalinity, sulfate, nitrate, nitrite, fluoride, phosphate, fe, mn, cu, ...

in recent years, the needs of the internet are felt in lives of all people.  accordingly, many studies have been done on security in virtual environment. old technics such as firewalls, authentication and encryption could not provide internet security completely; so, intrusion detection system is created as a new solution and a defense wall in cyber environment. many studies were performed on d...

internet applications spreading and its high usage popularity result insignificant increasing of cyber-attacks. consequently, network security has becomea matter of importance and several methods have been developed for these attacks.for this purpose, intrusion detection systems (ids) are being used to monitor theattacks occurred on computer networks. data mining techniques, machinelearning, ne...

porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. nowadays, using intelligent techniques has become a popular method for porosity estimation. support vector machine (svm) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...

objectives in order to increase the classification accuracy of airs, this study introduces a new hybrid system that incorporates a support vector machine into airs for diagnosing tuberculosis. background tuberculosis (tb) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. diagnosis based on cultured specimens is the...

different approaches have been proposed for feature selection to obtain suitable features subset among all features. these methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. the objective functions are divided into two main groups: filter and wrapper methods.  in filter methods, features subsets are selected due to some measu...

segmentation and three‑dimensional (3d) visualization of teeth in dental computerized tomography (ct) images are of dentists’ requirements for both abnormalities diagnosis and the treatments such as dental implant and orthodontic planning. on the other hand, dental ct image segmentation is a difficult process because of the specific characteristics of the tooth’s structure. this paper presents ...

Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...

We rederive a form of Joachims’ ξα method for tuning Support Vector Machines by the same approach as was used to derive the GACV, and show how the two methods are related. We generalize the ξα method to the nonstandard case of nonrepresentative training set and unequal misclassification costs and compare the result to the GACV estimate for the standard and nonstandard cases.