1443 results about "Relevance analysis" patented technology

An application service provider (ASP)-based interface and system for analyzing performance and costs of respective enterprise information technology assets from the correlation of metrics data of enterprise SNMP-enabled devices.

Replica correlation processing, and associated representative signal-data reduction and reconstruction techniques, are used to detect signals of interest and obtain robust measures of received-signal parameters, such as time differences of signal arrival and directional angles of arrival, that can be used to estimate the location of a cellularized-communications signal source. The new use in the present invention of signal-correlation processing for locating communications transmitters. This enables accurate and efficient extraction of parameters for a particular signal even in a frequency band that contains multiple received transmissions, such as occurs with code-division-multiple-access (CDMA) communications. Correlation processing as disclosed herein further enables extended processing integration times to facilitate the effective detection of desired communications-signal effects and replication measurement of their location-related parameters, even for the communications signals modulated to convey voice conversations or those weakened through propagation effects. Using prior, constructed, signal replicas in the correlation processing enables elimination of the inter-site communications of the signal representations that support the correlation analyses. Reduced-data representations of the modulated signals for voiced conversation, or for the variable components of data communications, are used to significantly reduce the inter-site communications that support the correlation analyses.

A system, method and computer program product for short-term forecasting of future retail performance are described herein. The system includes a Web-based graphical user interface, a weather history database and a weather forecast database. The method and computer program product allow users (e.g., retail managers and the like) to produce maps and related charts, using weather and sales history correlation analyzes, indicating weather favorability for specific retail products in specific geographic areas during specific future (and past) time periods. The weather favorability maps thereby facilitate retail-based advertising, allocation, placement, promotion and staffing decisions.

The invention discloses a method for vibration online monitoring and fault diagnosis of a power transformer. The surface vibration of an oil tank of a transformer, the voltage, the current and the oil temperature of the transformer, and the switching values reflecting the on-states of a vibration source fan and the oil tank of the transformer are taken as basic monitoring parameters to be monitored; after signal conditioning is performed on the monitoring parameters, continuous synchronous waveform data sampling, processing and saving are performed; then the processed waveform data are continuously displayed in real time; signal decomposition, multi-parameter correlation analysis and characteristic vector magnitude extraction are performed on the waveform data; and then various characteristic vector thresholds of a specific transformer are compared to analyze and diagnose the operating state and the fault of the transformer. With the method, the operating state of the power transformer can be monitored in real time, and early warning as well as the analysis and the diagnosis of the fault condition of the transformer are provided, thus guaranteeing the secure and stable operation of the transformer.

The invention relates to a multiple-template matching identity recognition method based on an ECG (Electrocardiogram) under an electrocardiogram abnormality state, and belongs to the technical field of biological characteristic identity recognition. The ECG data of a user to be recognized is compared with the data of a registered user in a template library to obtain an identity recognition result. The key technology of the method comprises the following steps: carrying out electrocardiosignal preprocessing for eliminating noise interference; carrying out electrocardiosignal decomposition to separate an electrocardiogram waveform of each period; carrying out standardized processing for independently achieving standardization on time and amplitude scales; carrying out characteristic extraction: in the step, characteristics are extracted by wavelet transform, and clustering analysis is carried out by an ISODATA (Iterative Self-organizing Data Analysis Techniques Algorithm) so as to construct an ECC template library; and carrying out correlation analysis: in the step, correlation between ECG test data and each template is calculated, an optimal matching template is selected, and finally, an identity recognition result is obtained. The multiple-template matching identity recognition method provided by the invention utilizes the intrinsic electrocardiosignal of a human body to recognize an identity, and the ECG data under the abnormality state is considered.

Computer-implemented methods are described for, first, characterizing a specific category of information content—pornography, for example—and then accurately identifying instances of that category of content within a real-time media stream, such as a web page, e-mail or other digital dataset. This content-recognition technology enables a new class of highly scalable applications to manage such content, including filtering, classifying, prioritizing, tracking, etc. An illustrative application of the invention is a software product for use in conjunction with web-browser client software for screening access to web pages that contain pornography or other potentially harmful or offensive content. A target attribute set of regular expression, such as natural language words and/or phrases, is formed by statistical analysis of a number of samples of datasets characterized as “containing,” and another set of samples characterized as “not containing,” the selected category of information content. This list of expressions is refined by applying correlation analysis to the samples or “training data.” Neural-network feed-forward techniques are then applied, again using a substantial training dataset, for adaptively assigning relative weights to each of the expressions in the target attribute set, thereby forming an awaited list that is highly predictive of the information content category of interest.

The invention provides an industry dictionary generating method and an industry dictionary generating device. The method comprises the following steps of: acquiring a document collection corresponding to the initial industry glossaries according to the initial industry glossaries; acquiring candidate glossaries according to the document collection; performing industry relevance analysis on the candidate glossaries to acquire relevant candidate glossaries; performing co-occurrence analysis and incidence relation excavation on the relevant candidate glossaries to generate industry vocabularies; and adding the industry vocabularies into industry dictionaries. Due to the adoption of the technical scheme, the industry dictionaries can be generated, and the problems of high cost, low efficiency and the like which are generated when workers search the industry vocabularies in the prior art are solved.

The invention relates to an intelligent processing method for warning information of a combined power grid. The method comprises the following steps: the combination of an internal expert knowledge base and an external rule table, a multilayer-definition and analysis method of inter-signal incidence relation, and a definition method for both the rule table and an auxiliary signal table of ensuring relevance analysis completeness. According to the invention, an expert system principle and a control strategy are adopted to design the internal expert knowledge base so as to perform real-time analysis of various abnormalities and failures of the power grid; the external rule table is used for providing an analysis rule for the relevance of the abnormalities or failures of the power grid and SCADA (Supervisory Control And Data Acquisition) warning, so as to realize the external definition of the rule; the combined reasoning of both the internal expert knowledge base and the external rule table can ensure the completeness and accuracy of the signal analysis to the utmost; and the physical space attribute of signal is defined into such five layers as local station, local interval, local equipment, upper-level equipment and lower-level equipment, and the property of abnormalities or failures of the power grid is described in a multilayer way. Moreover, the auxiliary signal table is added into the external rule definition to ensure the completeness of the relevance signal of a warning analysis system.

The invention relates to a data mining-based plate shape control key process parameter optimization system, and belongs to the technical field of automatic control of cold continuous rolling plate shape. The data mining method is adopted for acquiring key process parameter optimization settings which can meet the good cold continuous rolling plate shape. The system is characterized by comprising the following functional modules: an actual data acquisition and storage module, a process data pre-processing module, a process data storage module, a process data correlation analysis module, a process data clustering analysis module, a process data association rule analysis module, an optimization result generating module and an optimization result application module. The system has the advantage that the good plate shape can be obtained by applying the plate shape control system. The method avoids endless theoretical research on plate shape control and fully utilizes actual plate shape control process data containing successful operation experience of field operators, and the plate shape process parameter settings which can obtain the good plate shape are acquired by data mining, so the plate shape qualification rate and the finished product rate of cold continuous rolled strip steel are improved.

Information of failure events from various network devices and service objects is written into original event list. Correlation analysis is carried out for events read by analyzing and controlling engine from the original event list according to levels of original event and selection of classes. The dynamic analytical algorithm synthetically handles information in each area such as scene of historical fault analysis, dynamic performance parameters of network, dynamic topology information and time character of event etc. comparing with prior art, the invention overcomes disadvantages of overlooking information of dynamic network state, dependent on preset rule and lack of auto study ability etc. The invented method provides effective correlation analysis, fault reason analysis and location in real time when storm of network fault happens.

Processing of genomic data is facilitated utilizing correlation analysis of mapped data sets, each data set including genomic data mapped and ordered relative to a genomic coordinate system. Correlation analysis identifies at a nucleotide level nucleotide positions wherein at least one nucleotide locus of each data set correlate. The analysis includes for each data set, selecting a nucleotide locus thereof closest to one end of the coordinate system, comparing the selected nucleotide loci for correlation, and if so, outputting results of the comparing, and updating the selected nucleotide loci by identifying the data set having a next nucleotide locus closest to the one end of the coordinate system, and inserting that next locus into the group of selected loci, and repeating the comparing for the newly selected loci. The process is repeated until nucleotide loci of the mapped data sets are compared and results of the comparison are output.

The invention discloses a method for predicting the size of acceleration condition in-vehicle noise contribution. The method comprises the following steps that a vibration source generating in-vehicle noise and the transfer path thereof are measured so as to obtain a noise fitting model; and the excitation source or the transfer function in the noise fitting model is modified so as to predict the size of contribution of the corresponding noise excitation source or the transfer function on the in-vehicle noise. The in-vehicle noise model is established by using the measured acceleration excitation source and the noise transfer function thereof and correlation analysis is performed on the relevant excitation source, the path transfer function and the noise frequency band to determine the strongly correlated vibration source of the in-vehicle noise and the path transfer function thereof so as to perform troubleshooting, and the method is simple and rapid, the computing burden can be substantially reduced and the processing efficiency can be enhanced.

The invention, which belongs to the data processing technology, discloses a method for constructing a big data platform of government affairs. The method comprises; step one, carrying out an information resource catalog carding analysis: to be specific, carrying out information carding and a relevance analysis of information to form an information resource directory and information demanding and sharing; step two, carrying out government affair big data collection and integration; to be specific, according to the information resource directory, carrying out collection and integration of data resources to form a government affair big data set; step three, carrying out sharing and exchanging of government affair big data; to be specific, carrying out exchanging and sharing between government affair big data; and step four, carrying out an application service of the government affair big data; to be specific, building an application model, digging effective information, and pushing the effective information on needs. The method has the following advantages: government affair data can be dug, analyzed, integrated, and applied effectively and thus integration of electronic information and geographic information technologies can be realized, so that promotion and application of the smart city concept can be realized.

The invention dislcoses a single-phase earth fault line selection method based on transient state high-frequency component correlation analysis. The method comprises the steps that whether or not a single-phase earth fault happens is judged according to the magnitude of a busbar zero-mode voltage instantaneous value, db10 wavelets are adopted for performing five-layer wavelet packet decompositionon zero-mode current of two work frequency periods after each feeder line fault, after the minimum frequency band is removed, node wavelet packet deposition coeffiences are reconstructed and summeredto obtain a fault transient high-frequency capacitance-current component, and a correlation coeefient matrix M between every two feeder lines is obtained; Si is set as a correlation accumulation coefficient for the ith feeder line fault transient high-freuqency capacitance-current component, when rho ij is larger than rho set, Si is equal to 1, 1 is subtracted from Si, and a correlation accumulation coefficient matrix S can be obtained; if Si is larger than 0 constantly, the busbar breaks down; if Si of only one feeder line is smaller than 0, the circuit is a fault circuit; if Si is smaller than 0 constantly, the circuit with the maximum high-frequency-band wavelet packet energy sum is determined as the fault circuit. According to RTDS simulation experimental verification, the method has the good accuracy, adaptability and the like.

The invention discloses a real-time acoustic emission detection method for thermal barrier coating damage and a failure process thereof, which comprises the following steps that: a thermal barrier coating sample and an acoustic emission sensor are connected and coupled; a load is imposed on the thermal barrier coating sample, the acoustic emission sensor receives an acoustic wave signal emitted from the sample; the received acoustic wave signal is carried out through wavelet transform to obtain a wavelet energy spectrum coefficient distribution map, the damage pattern of the signal is determined according to the wavelet energy spectrum coefficient distribution map; the quantitative analysis of the damage is performed according to a relationship curve that the number of acoustic emission signal incidents of each damage pattern changes with the imposed load; a signal component under the scale where the maximum value of the wavelet energy spectrum coefficient is located is extracted, the time difference that the signal component reaches each sensor is calculated by a correlation analysis method, and the position of a damage source is determined by a time difference position method. The method can simply and quickly make a real-time detection to the damage of the thermal barrier coating material and also contributes to the accurate forecast to the life of the thermal barrier coating at the same time.

The invention discloses an objective evaluation method of no-reference video quality weighted by key frame image quality. The method comprises the steps of: firstly, preliminarily selecting a key frame according to a movement intensity method weighed by a human eye interest, then dividing the preliminarily selected key frame into a scene switching type key frame and a non-scene switching type key frame by correlation analysis; evaluating image quality of the non-scene switching type key frame, subdividing the non-scene switching type key frame into a content change type key frame and a quality change type key frame according to an evaluation result; finally carrying out weighted summation calculation on single frame quality by using a duration factor and a deterioration frequency factor of the quality change type key frame, and obtaining the quality evaluation result of an entire video sequence. According to the objective evaluation method, the defect that then existing evaluating technology cannot be coincided with an actual subjective feeling; computation complexity can be reduced on the premise of ensuring the evaluating performance; the objective evaluation method is suitable for automatic evaluation of various video applications of an existing network, simple in operating steps and easy to integrate.

The invention provides a city short-term water consumption prediction method based on a least square support vector machine model. The method comprises the following steps that preprocessing is carried out on historical water consumption; correlation analysis is carried out; a least square support vector machine method is adopted for setting up a city short-term water consumption predicting model, and time sequence combinations of the historical water consumption with correlation coefficients larger than set values are selected to serve as a training sample set for training; the city short-term water consumption predicting model is adopted for carrying out prediction in real time; prediction errors are calculated, and if the prediction errors do not meet the prediction accuracy requirement, the city short-term water consumption predicting model is improved. According to the city short-term water consumption prediction method, preprocessing is carried out on the historical water consumption, an original change law is kept as much as possible, and therefore the prediction accuracy can be improved; as the least square support vector machine method is adopted, the problem of nonlinearity of a water supply system and the problem that an accurate model can not be set up are solved; weather data and/or holiday factors are considered comprehensively, and the prediction accuracy is improved.

The invention discloses a model updating method based on strain modal shape correlation. The specific steps are as follows: step 1), establishing a finite element model of a structure and analyzing the finite element model; step 2), performing experimental design and analysis; step 3), extracting a finite element simulation strain mode; step 4), performing correlation analysis: adopting a model confidence factor, and analyzing the correlation between the finite element model and the strain modal shape of an experimental test; step 5), selecting a mode to be modified; step 6), selecting a parameter to be identified; step 7), constructing a modification target; and step 8), performing modified iteration. According to the model updating method based on the strain modal shape correlation provided by the invention, by selecting an appropriate unit type, the obtained finite element model of the structure provides a reference model for strain response calculation; by selecting an appropriate strain mode to be modified, parameters to be modified and an optimum design method, the modified finite element model can better reflect the strain response of the structure; and the accurate finite element model is beneficial to the subsequent structural dynamic optimization design based on the finite element model, and the development of structural health monitoring and structural response prediction and so on.

The invention relates to a method used for extracting key characteristics in flotation froth image analysis. The method of the invention establishes a flotation froth image collecting platform, on the basis of acquiring froth images with an industrial camera, extracts color feature corresponding to red intensity and H intensity in RGB and HSV color spaces, combines morphologic operations and a watershed method to segment the froth images and extract size characteristics, calculates froth total reflection points to extract bearing capacity feature and adopts an image block correlation analyzing method to extract froth speed feature. The method of the invention can be used for analysis of flotation froth images and estimation of technological parameters and recovery percent in mineral floating process, thus realizing optimization of floatation production operation and reducing the waste of mineral resources.

The invention belongs to the cross-media information technology field and particularly is an image optimization clustering method based on the typical correlation analysis. The invention mainly adopts the typical correlation to analyze while considering content characteristics of media data in various modes, maps the characteristics of the media data in various modes to an isomorphism sub-space of a united dimension through the sub-space mapping algorithm and obtains the final clustering result through optimizing clustering algorithm. The invention overcomes single-mode characteristic limitation in the multimedia field where only data is used, effectively solves the isomerism problem of the media data in various modes on the bottom layer characteristics, realizes the united measurement of the media object information between various modes, obtains results which are more accurate, more effective and more comforted to the needs in the large scale image data and has a wide application value in the cross-media processing and the retrieval field.

The invention discloses an automatic identification method for the topology of a low-voltage transformer area, belongs to the field of distribution automation in power systems, is applied to power distribution area monitoring and is realized based on a low-voltage power supply network. A branch terminal is arranged in a power distribution box in the power supply network, and the branch terminal collects feature information of an incoming line and an outgoing line in the power distribution box and transmits the feature information to an upper computer through a communication channel; and the upper computer automatically identifies area topology by utilizing correlation analysis according to the feature information. The invention has the beneficial effects that the topological relation between the transformer area distribution boxes is analyzed by utilizing the correlation, so that the reliability and the accuracy of judging the transformer area network topology are improved; incoming lines and outgoing lines of the distribution box are characteristic information acquisition points, and a plurality of pieces of characteristic information are acquired; the robustness is high, the influence of abnormal data can be effectively reduced, and the topology identification accuracy is improved; no influence is caused on a power grid and a user, and the safety is high.