Modern statistical analysis often involves large amount of data from many application areas with diverse data types and complicated data structures. This paper gives a brief survey of certain large-scale applications. In addition, this paper compares a number of data mining tools in the study of a specific data set which has 1.4 million cases, 14 predictors and a binary response variable. The s...

Data from the urban renewal experience in Syracuse, New York are used to examine the impact of race on patterns of intra-urban migration. The results show that, overall, the migration patterns exhibited an exponential decay in frequency with increasing distance. Both blacks and whites display this pattern, but blacks tend to cluster more closely around the point of origin. Indirect evidence is ...

Change in urban construction land use is an important factor when studying urban expansion. Many scholars have combined cellular automata (CA) with data mining algorithms to perform relevant simulation studies. However, the parameters for rule extraction are difficult to determine and the rules are simplex, and together, these factors tend to introduce excessive fitting problems and low modelin...

Understanding and forecasting urban Air Quality (AQ) is not only a multifaceted and computationally challenging problem for machine learning algorithms, but also a difficult task for human-decision makers: the strict regulatory framework, in combination with the public demand for better information services poses the need for robust, efficient and, more importantly, understandable forecasting m...

Advanced technology in GPS and sensors enables us to track moving objects, such as human beings, animals, vehicles. These mobility data as historical activity data of moving objects, in some degree can reflect some internal and external features of moving objects, how to use the massive high-precision mobile data identify potential and meaningful pattern is the current hot spots and is also a s...

Data mining refers to the extraction of knowledge from large amounts of data using pattern recognition, statistical methods, and artificial intelligence. The decision tree method, a well-known data mining technique, is used to extract decision rules because using it, we can understand the grounds of classification or prediction. The decision tree method thus can be used to analyze spatial data....

Industrial and mining activities are recognized as major sources of soil pollution. This study proposes an index system for evaluating the inherent risk level of polluting factories and introduces an integrated risk assessment method based on human health risk. As a case study, the health risk, polluting factories and integrated risks were analyzed in a typical industrial and mining gathering a...

The extraction of ore and minerals by underground mining may induce ground subsidence phenomena. These phenomena produce several types of ground movement like horizontal and vertical displacements, ground curvature and horizontal ground strain at the surface, and associated building damage in urban regions. The influence function is a well-known and efficient method for the prediction of these ...