significant advantages of intermodal and containerized transport have increased the global interest to this mode of transportation. this growing interest is reflected in the annual volume of container cargo growth. however, the container transport inside iran does not have a proper place. comparing the count of containers entering and leaving ports with the statistics obtained from railway and ...

The Decision Tree algorithm is a data mining method that often applied as solution to problem for classification. C5.0 has several weaknesses, including: the and other decision tree methods are biased towards modeling whose features have many levels, some problems model can occur such over-fit or under-fit challenges, big changes logic result in small training, experience inconvenience, imbalan...

The present paper aims at constructing the decision tree for a given database which adopts an improved ID3 decision tree algorithm to implement data mining in order to predict the output. The database is generated using the sampling techniques and the classification algorithm is applied on the samples. The obtained results are compared with experimental results in order to verify the validity a...

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used d...

decision trees as one of the data mining techniques, is used in credit scoring of bank customers. the main problem is the construction of decision trees in that they can classify customers optimally. this paper proposes an appropriate model based on genetic algorithm for credit scoring of banks customers in order to offer credit facilities to each class. genetic algorithm can help in credit sco...

decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. the resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. the most comprehensible decision trees have been designed for perfect symbolic data. classical crisp decision trees (dt) are widely applied to classification t...

Results of damage prediction in buildings can be used as a useful tool for managing and decreasing seismic risk of earthquakes. In this study, damage spectrum and C4.5 decision tree algorithm were utilized for damage prediction in steel buildings during earthquakes. In order to prepare the damage spectrum, steel buildings were modeled as a single-degree-of-freedom (SDOF) system and time-history...

the prediction of liquefaction potential of soil due to an earthquake is an essential task in civil engineering. the decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. c4.5 is a known algorithm widely used to design decision trees. in this algorithm, a pruning process is carried out to solve the problem of the...