nitrogen is produced mainly from its most abundant source, the air, using three processes: membrane, pressure swing adsorption (psa) and cryogenic. the most common method for evaluating a process is using the selection diagrams based on feasibility studies. since the selection diagrams are presented by different companies, they are biased, and provide unsimilar and even controversial results. i...

in this article, a multi-objective memetic algorithm (ma) for rule learning is proposed. prediction accuracy and interpretation are two measures that conflict with each other. in this approach, we consider accuracy and interpretation of rules sets. additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. this...

background: it is estimated that major depression disorders constitute 8.2% of years lived with disability (ylds) globally. the repetitive transcranial magnetic stimulation (rtms) and electroconvulsive therapy (ect) are two relative common interventions to treat major depressive disorders, especially for treatment resistant depression. in this study the cost- effectiveness and cost-utility of r...

As the number of networked computers grows, intrusion detection becomes an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents the work to test and improve the performance of an intrusion detection system based on C-fuzzy decision tree, a new class of decision tre...

The techniques of combining the results of multiple classification models to produce a single prediction have been investigated for many years. In earlier applications, the multiple models to be combined were developed by altering the training set. The use of these so-called resampling techniques, however, poses the risk of reducing predictivity of the individual models to be combined and/or ov...

Ulilizing data mining tasks such as classification on spatial data is more complex than those on non-spatial data. It is because spatial data mining algorithms have to consider not only objects or interest Itself but also neighbours of the objects in order to extract useful and Interesting patterns. One or classilication algorithms namely the 103 algorithm which originally designed for a non-sp...

Credit risk prediction is an important problem in the financial services domain. While machine learning techniques such as Support Vector Machines and Neural Networks have been used for improved predictive modeling, the outcomes of such models are not readily explainable and, therefore, difficult to apply within financial regulations. In contrast, Decision Trees are easy to explain, and provide...