34 results about "Rank analysis" patented technology

The predictive asset ranking system and process quantifies the condition of major components and sub-components of a property based on a systematic comparison of one major component against another utilizing analytical hierarchy analysis. The predictive asset ranking may be expressed as a value or score that may be used as a benchmark to compare one property to another property. The predictive asset ranking process applies multiple analytical hierarchies to the various attributes of a property. The analytical hierarchy may be based on an attribute weighing process and may include a series of qualitative questions indicative of attributes of the property. The predictive asset ranking system may be dynamic and may be customized for the particular asset being evaluated. When the system is customized, the process may automatically recalculate the weights and redistribute the points used in the predictive asset ranking analysis.

The present invention discloses an intelligent social network recommender system. The system comprises: a data obtaining module and a data processing module, wherein the data obtaining module is used for carrying on webpage data crawling and storing the data into a database, and the data processing module is used for carrying on website data crawling, establishing a social network with a user as a node and an interaction of users as an edge relationship, wherein one user edge relationship is occurred by generation of one interaction of the users in the network, otherwise no user edge relationship, and the users with the edge relationship present a neighbor relation and a establishment of a communication network of the social network is finished; and dividing communities by a community division algorithm, selecting an influential index according to the emphasis in different social networks, to analyze influential ranking on the user with similar characteristics in the single community, carrying on a classification of a user value with analysis of a user interest sticker, and plotting out a larger community to carry on analysis of influetial value on the users, thereby realizing an advantage of improving the identification accuracy of important users in the social network.

The invention provides an ultrasonic image low-rank analysis based thyroid lesion image identification method. The method comprises three steps of extracting and describing image block-shaped features based on superpixel hierarchy partition: extracting image features in a multi-scale and hierarchical way by taking a superpixel as a unit, removing redundant information of the image by virtue of the superpixel, lowering the complexity of a subsequent image processing task, and giving consideration to acquisition of global and local information; identifying thyroid based on feature space low-rank reconstruction error analysis: according to the low-rank property of image structure information, calculating the similarity between test data and a dictionary in a manner of optimizing a lowest rank, calculating a reconstruction error, and identifying a thyroid region in combination with a graph-cut segmentation algorithm; and detecting a thyroid lesion based on local low-rank decomposition: dividing a data matrix into a matrix with the low-rank property and an error matrix with the sparsity by adopting a low-rank decomposition method, calculating a sparse error, performing significance detection, and determining a lesion region.

A system and method for mark-up language document rank analysis that may be performed automatically and that may also determine one or more differences between mark-up language documents with regard to their relative rank.

Methods and systems for ranking analysis results based on user perceived problems of a database system are described. During operation, an embodiment may receive a designation of a perceived database system performance problem from a user, wherein the problem is associated with one or more database system metrics. Next, the embodiment may determine a set of recommendations for alleviating the perceived database system performance problem. The embodiment may then analyze the set of recommendations to determine, for each recommendation in the set of recommendations, an impact the recommendation is expected to have on the one or more database system metrics. Finally, the embodiment may rank the set of recommendations according to the impact each recommendation is expected to have on the perceived database performance problem.

A method and apparatus for improving search results is provided. The method works by delineating sections of a document that are not relevant to the main content. The document content is subjected to ranking analysis in entirety. In response to a query results are recalled omitting terms included in the no-recall sections. Terms in the no-recall sections are not used in titles and abstracts of the results. The results are ordered at least in part by the rankings attributed to the identified no-recall sections.

A method of improving operation of a petroleum reservoir using geotechnical analysis includes classifying a petroleum reservoir using a Reservoir Ranking Analysis (RRA) and then making one or modifications to the operation of the reservoir. RRA classification includes establishing reservoir classification metrics for at least resource size and recovery potential, and optionally profitability. The reservoir can be classified based on at least one metric in the profitability classification category, and also based on at least one metric in one or more of the resource size classification category or the recovery potential classification category. Classification of reservoirs can aid in reservoir management, planning, and development.

The invention provides a social network node influence sorting method and a system, which relate to the technical field of digital information processing. The method includes: collecting user personalhome page information, user posting information and user-to-user information, pretreating the personal home page information, user posting information and user-to-user information to form a trainingset and a test set; Then, according to the training set, establishing the transfer matrix model of the post, and performing simulation calculation of the transfer matrix model to obtain the optimal training parameters; Finally, according to the test set and the optimal training parameters, establishing a test transfer matrix for post forwarding, and calculating the test transfer matrix to obtain the ranking result of the influence of the social network nodes. The invention can discover the attention possibility of the hidden node so as to carry out influence ranking analysis on the data network whose dynamic information is incomplete and seriously missing. In the absence of social network data, it can more accurately analyze the impact of social network nodes.

A method of reducing rainwater and / or groundwater inflow and infiltration into a wastewater treatment collection grid. The method preferably involves the steps of (a) dividing the grid into a plurality of major subsystems, (b) determining flow depth levels in each major subsystem under dry and wet conditions, (c) using these wet weather and dry weather flow depth measurements to determine a volume flow ratio for wet versus dry conditions, (d) using these flow ratios to identify the particular major subsystem(s) in which the greatest amount of inflow or infiltration is occurring, and then (e) further dividing the highest ranking major subsystem(s) into smaller subsystems in which the same dry and wet weather level measurement and ranking analysis is preferably conducted to further isolate problem locations for surveillance, maintenance, and / or repair.

A system and method for mark-up language document rank analysis that may be performed automatically and that may also determine one or more differences between mark-up language documents with regard to their relative rank.

The invention discloses a real-time object tracking method based on video inter-frame low-rank associated information consistency. The method comprises the following steps: during the target object characteristic description period, giving position information in an initial video by a user at first and then performing characteristic description on a target object and a candidate region in a next frame by compressive sensing of local restrictions; during the inter-frame low-rank association analysis period, extracting key descriptions from a target object characteristic library to form a local characteristic library, and performing low-rank decomposition on the local characteristic library and the characteristic descriptions of the candidate region together to obtain a sparse matrix; calculating an inter-frame low-rank associated prior and cover mask; outputting a current target object position according to the sparse matrix and the inter-frame low-rank associated prior and cover mask; updating a target library, performing global low-rank analysis on a target characteristic library, and replacing the low-rank description with the best commonality with a current target object description. The method is capable of stably tracking a single object in the video for a long time in real time, and has the characteristics of high tracking speed, high tracking precision and the like.

The invention provides an applicant regional-ranking analysis system and an applicant regional-ranking analysis method. The system of the invention is based on a patent database, a user instruction module and a display terminal. The applicant regional-ranking analysis system comprises a patent database analysis special subject establishing module, an applicant region selection module, an applicant number selection module, a display control module and a result display module. The method comprises the following steps of: 1) establishing the patent database; 2) retrieving and establishing a patent analysis special subject in the patent database; 3) selecting the region of analyzed applicants from the patent analysis special subject by using the applicant region selection module; 4) selecting the number of the analyzed applicants in the patent analysis special subject by using the applicant number selection module; and 5) displaying the ranking diagram of the applicants in the selected region and number by using the display control module and the result display module. The system and the method can directly and quickly count the regional ranks of the applicants a user pays attention to.

A system and method for mark-up language document rank analysis that may be performed automatically and that may also determine one or more differences between mark-up language documents with regard to their relative rank.

The invention discloses an image feature extraction method based on low-rank robust linear discriminant analysis. The method aims to overcome the defect that an LDA algorithm is sensitive to noise and robustness is bad. According to the method, a low-rank technology and an LDA algorithm are combined, an image feature extraction method for low-rank robust linear discriminant analysis is provided, and for a group of noisy data, the noise in the data can be separated while a low-rank representation method is used for learning a low-dimensional subspace structure of the data. Therefore, low-rank analysis is introduced into the LDA algorithm, so that the robustness of the algorithm can be improved, the algorithm is insensitive to noise, and the robustness and the recognition performance of the LDA algorithm are further improved.

The invention belongs to the field of precision metering and computer application and relates to a rapid and simple method for rapidly evaluating the parallelism degree of a plane relative to a reference plane. The method comprises the following steps that: step 1, a measuring point set is acquired, a state element set, a feature row vector set and a boundary element set are constructed according to the measuring point set, and the position of a gauge is determined according to the measuring point set; step 2, two key points are acquired; step 3, an analysis matrix is constructed with the key point set; step 4, rank analysis is carried out, whether optimization is continued or not is determined, and an optimization strategy is determined; step 5, the analysis matrix and an analysis column vector are solved, so that an optimization direction is obtained; step 6, a new key point is solved, a measurement point coordinate set and the position of the gauge are updated, and the method enters the next circulation step; step 7, the flatness of the reference plane is calculated; step 8, flatness error t is compared with a given tolerance value TD, and whether the flatness is qualified or not is judged; and step 9, if the flatness is qualified, the parallelism error value of a plane to be measured is calculated; and step 10, parallelism error t' is compared with a given tolerance value T'D, and whether parallelism is qualified or not is judged.

The invention discloses a flame identification algorithm of low-rank analysis. First, video images are acquired by an infrared camera and preprocessed by Gaussian smoothing filter, and grayscale images are binarized. The external rectangle of a suspicious area of the current frame is extracted and zoomed in. The data of the external rectangle is used as a column vector. The data of external rectangles of a flame area of the continuous n-1 frame behind the current frame is extracted and zoomed to the same size, and the data of the frame is taken as column vectors frame-by-frame. All column vectors form a matrix D which his decomposed into the sum of a low rank matrix A and a sparse error matrix E. The singular value decomposition for the low rank moment A is obtained, and respective contribution rate is calculated by the square of the singular values. The number of singular values is determined by that the cumulative contribution rate is greater than the given threshold. The determined number is new rank rank(D) of the matrix D, and the boundary point theta* is obtained through experiments. An alarm is given off when the number is greater than or equal to theta*. A lot of experiments show that the algorithm has high recognition rate and robustness, and the method is proved to be effective.

The invention relates to a three-phase power distribution network observability analysis method based on a linear circuit, and belongs to the technical field of power system dispatching automation and power grid simulation. The method comprises the steps: firstly completing the modeling of various types of measurement of a three-phase power distribution network; secondly obtaining an unobservable branch circuit in a three-phase system based on the rank analysis of a measurement Jacobi matrix; and finally obtaining an observable island of the system according to an observability analysis result of the branch circuit. The method can achieve the linear voltage measurement and power measurement of triangular connection, can achieve the processing of the impact on the observability from a distributed power supply, and can achieve the processing of the observability analysis of a power distribution transformer level.

A method for mining user value of medicine purchased by users based on big data analysis is disclosed in the inventon. The method includes the following steps: S1, firstly, user interaction units, a member rank analysis system and a member classification system are respectively established in the whole member drug purchasing system, each time a member consumes and buys drugs in an Internet pharmacy, the types and prices of the drugs are stored in a large drug purchasing database through a storage module, and the system management module records the time when the member purchases the drugs andtransmits the records to the large drug purchasing database, which relates to the technical field of drug sales. A method for mining user value based on big data analysis of user purchasing medicine,the invention realizes the fast classification of the members according to the big data, achieves the purpose of mining the value of the members according to the members of different categories, realizes the mining of the drug purchase information of the members to increase the number of the members' re-purchase, thereby greatly facilitating the drug sales work of the Internet pharmacy.

The invention provides an ultrasonic image low-rank analysis based thyroid lesion image identification method. The method comprises three steps of extracting and describing image block-shaped features based on superpixel hierarchy partition: extracting image features in a multi-scale and hierarchical way by taking a superpixel as a unit, removing redundant information of the image by virtue of the superpixel, lowering the complexity of a subsequent image processing task, and giving consideration to acquisition of global and local information; identifying thyroid based on feature space low-rank reconstruction error analysis: according to the low-rank property of image structure information, calculating the similarity between test data and a dictionary in a manner of optimizing a lowest rank, calculating a reconstruction error, and identifying a thyroid region in combination with a graph-cut segmentation algorithm; and detecting a thyroid lesion based on local low-rank decomposition: dividing a data matrix into a matrix with the low-rank property and an error matrix with the sparsity by adopting a low-rank decomposition method, calculating a sparse error, performing significance detection, and determining a lesion region.

A method and apparatus for improving search results is provided. The method works by delineating sections of a document that are not relevant to the main content. The document content is subjected to ranking analysis in entirety. In response to a query results are recalled omitting terms included in the no-recall sections. Terms in the no-recall sections are not used in titles and abstracts of the results. The results are ordered at least in part by the rankings attributed to the identified no-recall sections.

The invention discloses a method for checking parameters of an activated sludge mathematical model. The method mainly includes the first step of constructing the activated sludge mathematical model and determining basic data for model parameter checking, the second step of screening the parameters, needing to be checked, of the activated sludge mathematical model, the third step of conducting identification and ranking analysis on parameter sets, needing to be checked, of the activated sludge mathematical model through the calculation methods of sensibility, a colinearity index gamma k and an identifiable degree rho k, the fourth step of solving the parameter sets by adopting the weighted error quadratic sum of four indexes of COD, NH4<+>-N, TN and TP of discharged water as an objective function according to the model so that checked model parameter sets can be obtained, and the fifth step of substituting the checked model parameter sets into the activated sludge mathematical model to carry out dynamic examination and examining whether parameter checking meets requirements or not. According to the method, the needed workload is small, calculation precision is high, the problem that the parameters influence one another is reduced or solved, and the method can be widely applied to checking parameters of various activated sludge treatment process mathematical models.

The invention discloses an applicant patent ranking analysis system and an applicant patent ranking analysis method. The system comprises a patent database, a patent subject establishment module, an applicant patent number ranking analysis module and a display module for displaying a ranking analysis result. The analysis method comprises the following steps of: 1) establishing the patent database by retrieving patent bibliographic databases of various countries according to a preset technical scheme; 2) retrieving patents in the patent database by adopting the patent subject establishment module; 3) processing information in a patent analysis subject library by adopting the ranking analysis module to acquire applicant patent number ranking information; and 4) displaying an applicant patent number ranking information map through a graph display unit in the display module, and controlling the display contents of the applicant patent number ranking information map by using a display control unit. The applicant ranking condition is intuitively and quickly reflected in a graphic form.

The present invention discloses an intelligent social network recommender system. The system comprises: a data obtaining module and a data processing module, wherein the data obtaining module is used for carrying on webpage data crawling and storing the data into a database, and the data processing module is used for carrying on website data crawling, establishing a social network with a user as a node and an interaction of users as an edge relationship, wherein one user edge relationship is occurred by generation of one interaction of the users in the network, otherwise no user edge relationship, and the users with the edge relationship present a neighbor relation and a establishment of a communication network of the social network is finished; and dividing communities by a community division algorithm, selecting an influential index according to the emphasis in different social networks, to analyze influential ranking on the user with similar characteristics in the single community, carrying on a classification of a user value with analysis of a user interest sticker, and plotting out a larger community to carry on analysis of influetial value on the users, thereby realizing an advantage of improving the identification accuracy of important users in the social network.

The invention belongs to the field of precision measurement and computer application, and particularly relates to a stable, fast and simple-form maximum inscribed cylinder diameter assessment method comprising the following steps that step 1: a measuring point set is acquired, and a feature row vector set, a boundary element set and a state element set are established according to the measuring point set; step 2: the measuring point corresponding to the minimum value of the state element set is taken as the key point and the measuring point number is added to the key point set; step 3: an analysis matrix and analysis column vectors are established according to the key point set; step 4: rank analysis is performed on the analysis matrix and an augmented analysis matrix so as to determine whether to continue optimization, eliminate the key point or terminate the program and obtain the optimal value; step 5: the analysis matrix and the analysis column vectors are solved so as to obtain the optimization direction; step 6: a new key point is solved by the pursuit problem, the measuring point state set is updated and the process enters the next cycle; and step 7: the program is terminated and the optimal value is obtained.

The invention relates to a method and a system for ranking analysis tools, and specifically discloses that the analysis tools are used to solve service requests for software performance problems. Ranking of analysis tools includes measuring multiple times to resolve multiple service requests for software performance issues after initiating a run of multiple analysis tools; capturing error groups across multiple service requests; together with time to resolve service requests and error groups storing the identification of multiple analysis tools; determining the average time for each of the multiple analysis tools to resolve each set of errors; using error groups to organize the multiple analysis tools into one or more categories; and using the category within each category Rank analysis tools by their average resolution time within the analysis tool.

The invention belongs to the field of precision metering and computer application, parts are evaluated by using a physical gauge in the form of a mathematical model, and the invention specifically relates to a digitized straightness evaluation method in any direction, which is fast, stable and simple. The method comprises the steps of: 1: obtaining a measurement point set, and establishing a boundary element set and a state element set according to the measurement point set; 2: establishing a feature row vector set according to the measurement point set and a corresponding normal vector; 3: adding a key point; 4: establishing an analysis matrix and an analysis column vector; 5: performing rank analysis on the analysis matrix and an augmented analysis matrix to determine whether to continueto optimize, remove the key point, or terminate the program; 6: calculating an optimization direction; 7: solving a new key point by a following problem, performing optimization step calculation, performing update according to the formula in the step 1 to enter the next cycle, or entering the next cycle according to the step 4; and 8: terminating the program and obtaining an optimal value.

The embodiment of the invention discloses a ranking analysis function processing method and device, electronic equipment and a storage medium, and the method comprises the steps: detecting that a target execution plan meets a preset ranking function optimization condition, and randomly distributing to-be-ranked data to a multi-thread system; performing preset ranking function processing on the to-be-ranked data to obtain initial ranking data, and deleting the initial ranking data according to preset ranking function data retention items to obtain initial deleted ranking data; summarizing the initial deletion ranking data to obtain middle ranking data, and distributing the middle ranking data to a plurality of threads; and performing preset ranking function processing on the middle ranking data according to the group information to obtain final ranking data, and deleting the final ranking data according to preset ranking function data retention items to obtain an execution result of the target execution plan. According to the method, the problem of high data distribution performance consumption in the data analysis process is solved, and the effect of effectively improving the performance of the analysis function in the processing process of the analysis function is achieved.

The invention belongs to the field of precision measurement and computer application, relates to a method for evaluating a hole shaft part by combining rank analysis and measurement data and particularly relates to a rank analysis-based rapid evaluation method for the gradient of a single reference plane. The method comprises the following steps of 1, acquiring a reference plane measurement point set and a measured element point set, establishing a feature row vector set and a state element set; 2, obtaining an initial key sequence number set; 3, establishing an analysis matrix and an analysis column vector; 4, carrying out rank analysis; 5, determining an optimizing direction; 6, solving a new key point, and updating the coordinates of the measuring point set; 7, judging whether the reference element evaluation meets a qualified condition or not; 8, pre-positioning the measured element point set; 9, updating a real-time state element set; 10, updating a key sequence number set of the tested elements; 11, establishing an analysis matrix and an analysis column vector; 12, carrying out rank analysis; 13, determining an optimizing direction; 14, solving a new key point, and updating coordinates of the measuring point set; and 15, carrying out qualification judgment.

The invention belongs to the field of precision metering and computer application and discloses a method for evaluating a part by combining an entity gauge with measurement data in a mathematical model form, and relates to a quick, stable, simple-form and digital method for evaluating straightness in a given plane, which comprises the following steps of: step 1, acquiring a measurement point set,and establishing a boundary element set and a state element set according to the measurement point set; step 2, establishing a feature row vector set according to the measuring point set and the corresponding normal vector; step 3, adding a key point; step 4, establishing an analysis matrix and an analysis column vector; step 5, rank analysis is performed on the analysis matrix and the augmented analysis matrix so as to determine whether optimization continues to be performed, key points are eliminated or a program is terminated; step 6, calculating an optimization direction; step 7, solving anew key point by using a chasing problem, performing optimization step calculation, updating according to the formula in the step 1, and entering the next cycle; or entering the next cycle accordingto the step 4; and step 8, terminating the program and obtaining an optimal value.