35 results about "Statistical cluster" patented technology

Provided are, among other things, systems, methods and techniques for forecasting information. One representative embodiment involves obtaining data that has been provided by each of a number of individual people; dividing the people into clusters by utilizing a statistical clustering technique; calculating statistics of the data in each of at least some of the clusters; and combining the statistics for such clusters so as to obtain a combination forecast.

A technique for monitoring source addresses through statistical clustering of packets is disclosed. In one particular exemplary embodiment, the technique may be realized by a method for monitoring source addresses through statistical clustering of packets. The method may comprise identifying at least part of a source address of a packet. The method may also comprise searching at least one recorded source address based on the at least part of the source address, the at least one recorded source address being organized into at least one cluster. The method may further comprise routing the packet if the at least part of the source address falls within one of the at least one cluster and the one of the at least one cluster contains at least a predetermined number of source addresses.

A method of grouping retail units of a set of units in a chain uses, store and market-specific characteristics, including store profitability, to group stores into like economic markets. The relation between profits and prices defines markets; stores facing the same relation, that is the same profit function, are in the same economic market. These stores can follow similar pricing and promotion strategies. Multiple regression analysis is used to identify those characteristics that affect the relation between prices and profits (not simply variables correlated with profits). Upon suitable standardization and weighting, these variables are subsequently used with a statistical cluster analysis to classify units in two markets. Based on the estimated relationship and homegenity valuations from discriminant analysis, new stores can be more accurately added to the appropriate group.

A method of grouping retail units of a set of units in a chain uses store and market-specific characteristics, including store profitability, to group stores into like economic markets. The relation between profits and prices defines markets; stores facing the same relation, that is the same profit function, are in the same economic market. These stores can follow similar pricing and promotion strategies. Multiple regression analysis is used to identify those characteristics that affect the relation between prices and profits (not simply variables correlated with profits). Upon suitable standardization and weighting, these variables are subsequently used with a statistical cluster analysis to classify units in two markets. Based on the estimated relationship and homegenity valuations from discriminant analysis, new stores can be more accurately added to the appropriate group.

The invention relates to a POI name determination system based on clustering and a method thereof, wherein the method comprises the following steps: capturing address data from network data, the address data includes name field and address information; clustering name fields corresponding to the same address information according to key words; counting frequency of the clustered name fields occurred in each cluster, using the frequency as a second frequency; determining the POI name of the cluster corresponding to the address information based on the second frequency. By the provided technical scheme, users can quickly and precisely search the POI name corresponding to the POI address at the same longitude and latitude, thereby improving the user experience.

The invention relates to an image segmentation processing method based on an area matching optimization K-means clustering algorithm, comprising steps of firstly extracting vehicle feature points of front and back frame images, and then comparing an area overlapping situation of front and back frame vehicles, extracting positions of the feature points in an area overlapping region and the positions of the rest feature points, respectively calculating a mean value of the two groups of the feature points as two types of initial clustering central points to be segmented, and then implementing K-mean segmentation, correcting a classification situation of the feature points in the area overlapping region according to an output clustering result, and meanwhile, judging whether the clustered vehicles are reasonable or not; and if not, re-clustering the clustering result and recounting clustering centres, ending clustering segmentation until the reasonable vehicles are found, and then feeding back a tracking result. The method is on the basis of area matching optimization, and adopts fixed clustering numbers to implement the segmentation; and vehicle targets obtained by the K-mean segmentation do not need the next round of matching treatment, thereby a processing speed is accelerated, and time is saved.

The invention provides a method for identifying the location of road intersections in trajectory data based on statistical clustering, including trajectory data coordinate projection conversion, and trajectory data simplification processing; for the simplified trajectory data, a multi-core parallel computing method is adopted, and the direction is turned according to the sampling point The sampling points in the change recognition road intersection area constitute a set of steering sampling points; the set of steering sampling points is used as input, and the adaptive statistical clustering algorithm is used to automatically divide the clusters, and the road intersections at different locations are separated; finally, For each turning sampling point cluster, the center position and radius of the minimum circumscribed circle covering the cluster are calculated by the minimum circumscribed circle fitting algorithm, and the center position and area range of the road intersection are represented by the center and radius of the minimum circumscribed circle .

The invention provides a method and device for judging the occupation distribution of clustered users. The method comprises the following steps: obtaining a plurality of pieces of position information of a user terminal on the basis of positioning information provided by the user terminal; distinguishing the working place information and the residence plate information from the plurality of pieces of position information; clustering a plurality of users which are on the basis of the same residence place information; carrying out statistics on the working place information of the clustered users; and judging the occupation distribution of the clustered users according to the working place information of the clustered users. According to the method and device provided by the invention, the position information of the users is obtained by utilizing the positioning information of the users and then working place information and the residence place information are further distinguished; the plurality of users on the basis of the same residence place information are clustered to obtain the working place information of the clustered users in a certain region; and the occupations of the users can be determined on the basis of the working place information so as to obtain the occupation information of the work in the region and then the occupation distribution is analyzed.