详情

Knowledge Discovery in Transportation Databases (KDITD)

项目名称：	Knowledge Discovery in Transportation Databases (KDITD)
摘要：	Over the years, Department of Transportation (DOT) agencies along with university laboratories have produced a large number of transportation system databases that cover a wide spectrum ranging from crash-traffic historical databases to pavement-material performance databases. The main goal of the knowledge discovery process, via the use of statistically-based, artificial intelligence-based or hybrid techniques, is to extract the knowledge buried within these databases. Knowledge discovery via statistic ally-based techniques is widely used. However, these techniques have severe limitations and constrains in extracting the knowledge due to the complexity of these databases. On the other hand, artificial intelligence-based methods such as artificial neural networks, fuzzy logic, and other various forms of data mining procedures offer a more efficient methodology for knowledge discovery. For example, artificial intelligence-based (AIB) methods are not constrained by the required functional form that is typically needed to be defined in advance for statistically-based (SB) methods. Appropriately combining the best features of SB and AIB methodologies can a yield a far more superior hybrid knowledge discovery (HKD) approach. Utilizing such hybrid approach can efficiently extract t he important features (i.e., useful knowledge) hidden in the complex transportation system databases. In this research study, we are proposing to appropriately combine the diverse expertise of the research team in order to develop an efficient HKD approach. The developed HKD approach will then be used to extract the hidden features within a wide spectrum of databases ranging from crash-traffic-driver related databases to pavement-material-performance related databases. It is expected that this research will help advance the proper utilization of the newly created information-based science (IBS) in transportation engineering.
状态：	Active
资金：	180000.00
资助组织：	Kansas State University Transportation Center
项目负责人：	Stokes, Robert W
执行机构：	Kansas State University Transportation Center
开始时间：	20050810
实际结束时间：	20120531
主题领域：	Data and Information Technology；Highways