Analysis Of The Road Traffic Accident Reason In Clustering

The fast growing of computer hardware, such as the powerful computers, data collection equipments and storage mediums promotes the development of database and information technology, and the abundant data in the large database makes it necessary to adopt the powerful data analyzing tools to solve the problem of abundant data and indigent information. The great gulf fixed between data and information requires to developing the data mining tools systematically to convert the data to the useful knowledge. The data mining is to distill the interesting knowledge from the data in the large database, and all these knowledge is connotative, undiscovered and potential useful information, and the achieved knowledge is expressed as concepts, rule, regularities, patterns and so on. The safe problem of transportation has already been widespread concern in the whole society. In order to reduce the occurrence of the traffic accident, Intelligent Transportation System(ITS) have been applied in other nations and its developing is more slowly in China than in Other Developed countries. The ITS needs for high information level, provides professional, multi-element, individuation service. All this is based on the advanced technique methods, management concepts and the service system With the development of the road transportation, the traditional transportation management by hand can not meet the practical demands nowadays. More and more attention is being paid to the application of telecommunication and computer technologies in transportation and thus it is developing faster and faster. ITS is applied more and more widely, and the transportation in China is going into an information, digital era. With the universality of the progress and automobile sharply developed in city, the safe problem of transportation is increasingly serious. In order to resolve it a new research and application field, ITS comes into being. One of the important question of ITS is the analysis to the traffic accident reason in the Intelligent Transportation System, in order to prevent from the similar trouble taking place again .More and more the information of the accident reason were collected . It is very easy to get a mount of traffic data, however, it takes both time and efforts to deal with these data in the traditional way. Maybe, useful knowledge is concealed in these data. Data mining is to find information from the vast amount of data. At present, data mining has been widely used in the business sphere, but hardly used during the traffic control system. By making the use of the clustering method in data mining and the technique of the Open Database Connectivity (ODBC) the paper carry on the analysis to the data about road traffic accident reason. This paper attempts to provide applying the cluster analysis to information of traffic data under the VC background. The main research is about the theory and methods of the cluster analysis. In the same time analyzing the reason how the road factor influence on the traffic accident. In recent years, data mining is applied more and more widely in many fields, such as the analysis of sequence, the classification and clustering of customers, cross-selling, detection of fraudulence, etc. Clustering, as one of the main techniques of data mining, becomes an increasingly hot topic. At present, many clustering algorithms are available, such as k-means, k-medoids, BIRCH, CURE, DBSCAN, STING, and so on. Although some of them have been applied successfully in some fields, many new challenges are emerging, such as the handling of large datasets and high-dimensional datasets, subspace clustering, clustering with constraints, clustering of data streams, etc. To solve these new problems, some strive to design brand new algorithms, while others try to improve existing algorithms. The core technology of analysis in traffic accident reason is data mining. As a new technology to process accident reason information, data-mining can extract, transfer, analysis and modulate the mass data in the traffic accident database, to get the key data helpful to management decision and help Transportation directing center to be intelligent in management. The tasks of data mining include association rules analysis, time series module,cluster analysis, classification and predication and so on. Clustering analysis, as a module and function of data mining, is the main content of this paper .Putting forward the method of the improvement, realize the accident reasons'clustering algorithm .In our study, we value the algorithms' practical application instead of their complexity and perfection. Another contents of this thesis are the ODBC technique. The ODBC is part of Microsoft Windows open the service system structure. It is the standard interface in the database interview. It is also provided as a standard interface when application program interview the relation database. The ODBC provided a set of API for the different database The program can apply the API to visit to any database that provides the ODBC to drive the procedure, In this way, the technology that is interview the different structure data source is realized .The ODBC is a kind of interview technique database that is in the under lying floor. The ODBC API cans make the program establish and control database from the under lying floor. In the same time it can complete some high function that the database technique can't complete. For example, establish and install the data source, constitution database size etc. The ODBC is the widest. At present it is the most successful standard in using for the related data connection. Most databases include not only the ODBC drive but also itself drive the procedure. Some database use the ODBC to drive the procedure. The database of ODBC also can easily transfer in the different database. If wanting to change database engine, the developer only needs to make the ODBC connect a new database of direction, but not to replace itself drive in the old appropriative procedure with the new appropriation database t drive. All of the main works in this thesis is following: l. Describe the data mining technique in detail, including the concept, process procedure, system construction, analyzing models, and the common technique, especially discuss the Partitioning Clustering used in clustering analysis in detail. 2. Systemically introduce the foundation knowledge of ODBC .The technique of...