Constraint - Based Urban Co - Location Model Mining

With the development of urbanization in the country, many city’s urban construction in full speed, one of the successful synthesis of a building can add important for the rapid development of the city. However, there are many examples of failure, defeated economy, cluttered living environment also restricts the development of the city. Select location and supporting the construction of facilities all affect the success or failure of a complex construction. So it is particularly important to use the spatial data mining technology for technology planning.But, in the traditional construction process, the have a great right to make recommendations on the construction planning advice. So, these recommendations of scientific and rational constraints are advancing to the policy makers, which can largely avoid defeat urban complex construction, for example, the increase in retained rational layout, or reduce the number of unnecessary supporting construction, avoid duplication, so that wasting the resources, it would get the most optimal solution. In recent years, the government has been increasing emphasis on data mining in Urban Planning, spatial data mining technology to solve spatial knowledge acquisition is also a great improvement, the study of the distribution of spatial data mining technology used in urban complex, to provide a theoretical basis for the site of a city complex in the city. Through the study of the urban complex, to get their location distribution of objects, thus the construction of the future city complex instructive.In this regard, I studied the following content: Compared the concept of data mining algorithms with space co-location pattern mining were introduced. (2) The related theories Mining Methods were consolidated. (3) With the use of co-location space constraints pattern mining theory. To analysis the city A complex objects. It was extracted, data processing. The main facilities of the central area of the Confucius Temple, conditional constraint to its various frequent pattern exists, Then rule extraction. User for residential area and the bank, primary school, KTV, etc. to get the spatial co-location pattern mining, and propose constraints. Strong demand for the residential area at the same time exclude primary and KTV and other entertainment venues appear in a region close. Mining results will be retained mode with residential and deleted with{KTV, primary mode}.For research aspects of algorithms based on co-location fully connected Mining Algorithm, thought algorithm is based on its internal relations generated, the whole algorithm is applied to connect the space co-location mode to Mining. First I extract the spatial object data, Then added user constraints to the classical Join-base space co-location pattern algorithm, so what we mining the co-location mode could be made mining more realistic. This will be based in city A, a city complex object for research, supplicate the method related with the constraints to get its co-location space pattern mining, excavated space co-location mode with a user constraints. Analysis the pattern mining, understand their distribution, so that guiding the construction of new urban complex.