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35 results about "Statistical cluster" patented technology
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Cluster analysis is a statistical data analysis tool used by companies to sort various pieces of information into similar groups. Companies may use mathematical algorithms or visual diagrams when creating a cluster analysis. The hierarchical-style analysis attempts to take one large group and break it down into several smaller groups.
Analysis and prediction of data using clusterization
InactiveUS8935198B1Accurate predictionReduce the impactFinanceDigital computer detailsData miningStatistical cluster
Owner:C4CAST COM
Information processing method for disease stratification and assessment of disease progressing
InactiveUS20040243362A1Reducing time spent repetitivelyFailure can be accuratelyMedical simulationMedical data miningInformation processingOptimal treatment
A digital computer system stratifies in a set of patients, based on a set of observations. The observations can include physical, biochemical, histological, genetic, and gene-expression data, among other types of information. Adjustments can be made to account for the possibility that observations of several patients may begin at different points in the progression of their respective disease processes. Once these adjustments are made, the data are subjected to a statistical cluster analysis. Each cluster of patients potentially represents a different disease stratum, with its own underlying cause, optimum therapy, and prognosis. Once the strata are defined and patients are assigned to them, adjustments to the data can be refined. The cluster analysis then can be repeated, and so an iterative process of stratification and staging takes place.
Owner:PROSANOS CORP
Method for assigning retail units to economic markets
ActiveUS20050108070A1Eliminate the effects ofReservationsResourcesRegression analysisComputer science
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.
Owner:REVENUE MANAGEMENT SOLUTIONS
A semi-automatic knowledge map construction method
ActiveCN109522418AImprove accuracyNatural language data processingSpecial data processing applicationsGraph spectraSemi automatic
The invention discloses a semi-automatic knowledge map construction method, Most of the existing relationship extraction methods rely on the pre-determined relationship type system, This process is complex and time-consuming, the invention is based on dependency analysis, aiming at several Chinese sentence patterns, combined with a semantic dictionary, While exporting open relationships, semantictagging of words in relation, The semantics of unknown words are inferred based on statistics, and the semantic relation patterns on a large number of corpus are statistically clustered to form a relation type system. In this process, most of the links are carried out automatically, in which the results of semantic annotation and relation clustering of unknown words can be checked manually. Compared with the existing open relation extraction method, the invention optimizes and expands, and the extraction of the open relation and the formation of the semantic relation type complement each other, so as to improve the accuracy rate of the two.
Owner:杭州费尔斯通科技有限公司
Technique for monitoring source addresses through statistical clustering of packets
InactiveUS20050138201A1Guaranteed maximum utilizationDigital computer detailsData switching networksData miningStatistical cluster
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.
Owner:RPX CLEARINGHOUSE
Statistical clustering-based road intersection position identification method in trajectory data
ActiveCN110909788AImprove detection efficiencyImprove detection qualityCharacter and pattern recognitionSatellite radio beaconingCluster algorithmAlgorithm
The invention provides a statistical clustering-based road intersection position identification method in trajectory data. The statistical clustering-based road intersection position identification method comprises the steps: performing trajectory data coordinate projection conversion and trajectory data simplification processing; for the simplified trajectory data, adopting a multi-core parallelcomputing mode, identifying sampling points in a road intersection area according to the steering change of the sampling points, and forming a steering sampling point set; taking the steering samplingpoint set as input, carrying out automatic division clustering by utilizing a self-adaptive statistical clustering algorithm, and stripping road intersections at different positions; and finally, foreach steering sampling point cluster, calculating a central position and a radius of a minimum circumscribed circle covering the cluster through a minimum circumscribed circle fitting algorithm, andrepresenting the central position and the regional range of the road intersection by using the center and the radius of the minimum circumscribed circle.
Owner:湖南博通信息股份有限公司 +1
POI name determination system based on clustering and method thereof
ActiveCN104572957AImprove experienceQuick searchWeb data indexingSpecial data processing applicationsLongitudeNetwork data
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.
Owner:BEIJING QIHOO TECH CO LTD
Method for retrieving three-dimensional object
InactiveCN101599077AImprove accuracySpecial data processing applicationsOptimal matchingRetrieval result
The invention discloses a method for retrieving a three-dimensional object, comprising the following steps: carrying out bipartite graph maximum matching on the three-dimensional retrieval object view sets and the view sets in a database, filtering the view sets not satisfying the preset matching conditions in the database to obtain the remaining view sets; carrying out bipartite graph optimal matching on the three-dimensional retrieval object view sets and each remaining view sets to acquire the distances between the three-dimensional retrieval object view sets and each remained view sets; sequencing each remaining view sets and outputting each sequenced remaining view sets as the retrieval results. The embodiment of the invention adopts pretreatment of statistical clustering, combines bipartite graph maximum matching and bipartite graph optimal matching to acquire the distances between the three-dimensional retrieval object view sets and each remaining view sets, thus improving the correctness of three-dimensional object retrieval, and simultaneously causing the three-dimensional object retrieval to be capable of not depending on collecting environment information, and the three-dimensional object retrieval method to be more vastly applied.
Owner:TSINGHUA UNIV
Feature selection impact analysis for statistical models
The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of feature additions and an evaluation metric for assessing the performance of a statistical model. Next, the system automatically builds treatment versions of the statistical model using a set of baseline features for the statistical model and feature combinations generated using the feature additions. The system then uses a hypothesis test and a fixed set of feature values to compare a baseline value of the evaluation metric for a baseline version of the statistical model that is built using the set of baseline features with additional values of the evaluation metric for the treatment versions. Finally, the system outputs a result of the hypothesis test for use in assessing an impact of the feature combinations on a performance of the statistical model.
Owner:MICROSOFT TECH LICENSING LLC
Image segmentation processing method based on area matching optimization K-means clustering algorithm
ActiveCN102375983AProcessing speedCharacter and pattern recognitionPattern recognitionMatch treatment
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.
Owner:SHANGHAI BAOKANG ELECTRONICS CONTROL ENG
Adaptive two-dimensional clustering-based signal pre-sorting method
ActiveCN108535704AImprove effectivenessSolve additional batchesWave based measurement systemsPattern recognitionArtificial intelligence
The invention discloses an adaptive two-dimensional clustering-based signal pre-sorting method. The method can be used for the signal pre-recognition of a new system radar in a complex environment. The method includes the following steps that: an antenna array is adopted to perform two-dimensional positioning on a target, so that distance and azimuth information can be obtained; the initial valuesof the thresholds of the distance and azimuth are set; similarity between the distance dimension and azimuth dimension of the target is calculated; two-dimensional clustering of the distance and azimuth is obtained according to the calculated similarity and thresholds; and the thresholds of the distance and the azimuth are adaptively adjusted, the average value of the similarity between the distance dimension and azimuth dimension after clustering is put into statistics until the average value is smaller than the threshold of the distance or the azimuth, and signal pre-sorting is completed. According to the adaptive two-dimensional clustering-based signal pre-sorting method of the invention, pre-positioning and pre-sorting are sequentially carried out, so that the limitations of traditional radar signal sorting are broken; and the two-dimensional clustering processing of the distance and azimuth is utilized, so that increasingly serious batch increase and batch missing phenomena of signal sorting can be eliminated, and therefore, the effectiveness of radar signal sorting can be improved.
Owner:GUIZHOU INST OF TECH
Non-cooperative voice communication received data invalid period identification method
InactiveCN107507630AAccurate identificationSimple calculationSpeech analysisVoice communicationZero-crossing rate
The present invention belongs to the communications and information technical field and relates to a method for processing received radio voice communication signals and information, in particular, a method for demodulating radio voice speech communication, and then performing data detection, segmentation and identification on the demodulated radio voice speech communication so as to identify periods of invalid signals such as noise and interference. According to the method, on the basis of the principles of statistical mathematics, statistical clustering analysis and fuzzy signal processing, a unified framework integrated processing method for identifying non-speech segments after receiving and demodulating non-cooperative radio voice communication, a detection method for finding sudden transient disturbance, a detection method for finding co-channel crosstalk disturbance from other radios, a speech signal and noise signal segment detection and identification method that does not depend on signal power strength and zero-crossing rate, a method for finding and identifying radio fault data, and a method for performing integrated identification on analog speech data and other digitally modulated data are provided.
Owner:嘉兴开泽电子设备有限公司
Technique for monitoring source addresses through statistical clustering of packets
Owner:RPX CLEARINGHOUSE
On-line monitoring method for working condition of gearbox of wind turbine generator
PendingCN114295367ARealize online monitoringMachine part testingCharacter and pattern recognitionGear wheelControl engineering
The online monitoring method for the working condition of the gearbox of the wind turbine generator comprises the following steps: acquiring fan operation data in different operation modes; grouping the fan data by using a method based on statistical clustering; identifying the operation mode of the wind turbine generator according to the data features of the grouping result; different types of gear states are distinguished based on different operation modes, grouped data are used for fitting a linear regression training model and outputting a gear speed ratio changing along with time, and the gear abrasion condition is quantitatively judged; obtaining an average gear speed ratio residual error according to a prediction result of the linear regression training model and the actual operation data; and fault identification and monitoring of different types of gearboxes are realized by analyzing the residual error of the average speed ratio, so that on-line monitoring of the working condition of the fan gearbox is realized.
Owner:HUANENG NEW ENERGY CO LTD +1
Voltage sag homologous identification method based on Pearson correlation coefficient and OPTICS
ActiveCN112784792AAvoid the problem that homologous identification features are too singleAccurate removalCharacter and pattern recognitionPattern recognitionCorrelation coefficient
The invention provides a voltage sag homologous identification method based on a Pearson correlation coefficient and OPTICS. The method comprises the following steps: S1, acquiring sag monitoring data recorded by a voltage sag monitoring device; S2, quantifying the sag monitoring data similarity based on a Pearson correlation coefficient; S3, obtaining homologous recognition features of the sag monitoring data, performing homologous clustering based on the homologous recognition features of the sag monitoring data through an OPTICS algorithm, and outputting a clustering result reachable graph, wherein the homologous recognition features comprise sag monitoring data similarity and sag duration; and S4, obtaining a clustering result cluster number based on a reachable graph sag number, and outputting a homologous recognition result. The problem that homologous identification features are too single is avoided, clusters of different densities can be found, the voltage sag homologous identification result is finally obtained, repeated redundant information can be effectively removed through the voltage sag homologous identification result, the real occurrence level of regional sag can be obtained, the value density of data is improved, and the intensity and difficulty of calculation and analysis are reduced.
Owner:HAINAN POWER GRID CO LTD ELECTRIC POWER RES INST
Method for assigning retail units to economic markets
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.
Owner:REVENUE MANAGEMENT SOLUTIONS +1
Evaluating input data using a deep learning algorithm
PendingUS20200251224A1Improve accuracyEnsure correct executionMedical data miningBiostatisticsData packHidden layer
The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing stabstical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.
Owner:KONINKLJIJKE PHILIPS NV
Method for assigning retail units to economic markets
Owner:REVENUE MANAGEMENT SOLUTIONS
Malicious traffic detection method and device in high-bandwidth scene based on frequency domain analysis
ActiveCN113794680AAccurate detectionImprove detection accuracyCharacter and pattern recognitionData switching networksHigh bandwidthFeature extraction
The invention provides a malicious traffic detection method in a high-bandwidth scene based on frequency domain analysis. The method comprises the following steps: carrying out data packet granularity feature extraction on network traffic to obtain a data packet granularity feature; encoding the features of the data packet granularity to obtain matrix representation, performing fitting operation to obtain a plurality of frames, and performing frequency domain analysis on each frame to obtain a corresponding frequency domain feature; calculating the power of the frequency domain features to obtain power representation, performing logarithmic transformation to obtain frequency domain feature representation, cutting and averaging the frequency domain feature representation to serve as the input of a statistical clustering algorithm, and outputting a clustering center; and calculating the distance between the frequency domain feature representation and the corresponding nearest clustering center, if the distance is greater than a predetermined multiple of a training error, determining that the flow corresponding to the frequency domain feature representation is abnormal flow, otherwise, determining that the flow is normal flow. The method has the advantages of high detection throughput, high precision, low time delay and the like, and malicious traffic can be accurately detected in a high-bandwidth scene while calculation overhead and storage overhead are considered.
Owner:TSINGHUA UNIV
A system and method for determining poi names based on clustering
ActiveCN104572957BImprove experienceQuick searchWeb data indexingSpecial data processing applicationsLongitudeNetwork data
Owner:BEIJING QIHOO TECH CO LTD
Evaluating input data using a deep learning algorithm
The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged intoa plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality ofhidden layers. The method further includes performing statistical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from eachstatistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.
Owner:KONINKLJIJKE PHILIPS NV
Image Segmentation Processing Method Based on Area Matching Optimal K-Means Clustering Algorithm
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.
Owner:SHANGHAI BAOKANG ELECTRONICS CONTROL ENG
A virtual machine load balancing method, management module and virtual machine cluster system
ActiveCN102594881BImprove resource utilizationIncrease resourcesTransmissionSoftware simulation/interpretation/emulationData centerResource utilization
The invention discloses a virtual machine load balancing method, a management module and a virtual machine cluster system, each manufacturer's virtual machine server is managed by the manufacturer's management module, and a management module responsible for cluster domain load balancing management is the main management module , the rest of the management modules are slave management modules, the master management module is responsible for statistics of virtual machine resource information and virtual machine load The collection and reporting of virtual machine resource information and virtual machine load information of the server, as well as the distribution of shared tasks, through the cooperation between the master and slave management modules, the virtual machine servers of different manufacturers can cooperate to share the load in the cluster domain, improving It improves the resource utilization and resource scheduling capabilities of the virtual machine server cluster in the data center.
Owner:ZTE CORP
A Method for Recognition of Road Intersections in Trajectory Data Based on Statistical Clustering
ActiveCN110909788BImprove detection efficiencyImprove detection qualityCharacter and pattern recognitionSatellite radio beaconingPattern recognitionCluster algorithm
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 .
Owner:湖南博通信息股份有限公司 +1
Method for retrieving three-dimensional object
InactiveCN101599077BImprove accuracySpecial data processing applicationsOptimal matchingRetrieval result
The invention discloses a method for retrieving a three-dimensional object, comprising the following steps: carrying out bipartite graph maximum matching on the three-dimensional retrieval object view sets and the view sets in a database, filtering the view sets not satisfying the preset matching conditions in the database to obtain the remaining view sets; carrying out bipartite graph optimal matching on the three-dimensional retrieval object view sets and each remaining view sets to acquire the distances between the three-dimensional retrieval object view sets and each remained view sets; sequencing each remaining view sets and outputting each sequenced remaining view sets as the retrieval results. The embodiment of the invention adopts pretreatment of statistical clustering, combines bipartite graph maximum matching and bipartite graph optimal matching to acquire the distances between the three-dimensional retrieval object view sets and each remaining view sets, thus improving the correctness of three-dimensional object retrieval, and simultaneously causing the three-dimensional object retrieval to be capable of not depending on collecting environment information, and the three-dimensional object retrieval method to be more vastly applied.
Owner:TSINGHUA UNIV
University innovation entrepreneurial ability evaluation method based on gray clustering
The invention relates to a university innovation entrepreneurial ability evaluation method based on gray clustering. The method includes defining a white function, adopting three kinds of statistic clusters of a high standard, a middle standard and a low standard to analyze the university innovation entrepreneurial ability and obtain numerical value classification of the high standard, the middle standard and the low standard of each index of each performance object.
Owner:WUXI NANLIGONG TECH DEV
Child detection frame filtering algorithm based on grid clustering
ActiveCN113361410ASolve the problem of many misjudgmentsAvoid misjudgmentCharacter and pattern recognitionVisual technologyMedicine
The invention relates to the technical field of computer vision, in particular to a child detection frame filtering algorithm based on grid clustering, and the method comprises the following steps: obtaining video data in a real scene through a camera, transmitting the video data to a computer through the camera, obtaining a target image, storing the target image, selecting a target camera, and pulling detection frame data corresponding to one week from a production environment; according to the child detection frame filtering algorithm provided by the invention, a detected human-shaped frame can be directly used as statistical data, then the average frame height in the grid range is obtained by using a grid clustering method, whether a child is a child is judged by using the average frame height and the target frame height, and meanwhile, the average frame height of each region in a target image can be judged; misjudgment caused by shielding is avoided, and the problem that due to the fact that many shielding and false detection exist in a real scene, statistical clustering is directly carried out through a detection frame, the whole data distribution is disturbed by an abnormal detection frame, and consequently many misjudgments of a child frame are caused is solved.
Owner:上海数川数据科技有限公司
Method and device for judging clustering user occupation distribution
ActiveCN105630951BData processing applicationsDigital data information retrievalResidenceDistribution method
Owner:BEIJING QIHOO TECH CO LTD
Clustering method of wind velocity usage habit of air-conditioner user
ActiveCN105354436AEasy to develop and designGood clustering methodSpecial data processing applicationsInformaticsStatistical analysisHabit
The invention relates to the air-conditioning technology. The problem that a system or method for statically analyzing a wind velocity usage habit of a user is inexistent at present is solved, the invention provides a clustering method of the wind velocity usage habit of the air-conditioner user. The technical scheme can be generalized as follows: firstly defining a plurality of clustering centers according to the selection of the user to the wind velocity; acquiring behavior data of the air-conditioner user through a database, and then acquiring the behavior data of each air-conditioner user from the database through the system, computing the usage rate of each wind velocity by the user, and computing the distance between the usage rate of each wind velocity by the user to each clustering center, comparing the distances, selecting the corresponding clustering as the classification of the user according to a distance rule, finally counting the user number of each kind through the system after the clustering, and outputting the usage preference of the user to the wind velocity on the whole. The method disclosed by the invention has the beneficial effects that the method is convenient for the developing and designing of the air-conditioner, and is suitable for the air-conditioning system.
Owner:SICHUAN CHANGHONG ELECTRIC CO LTD
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