47 results about "Point evaluation" patented technology

A system and method for estimating a metric of a proposed product from a document describing the product in an arbitrary degree of detail provides accuracy comparable to a function point assessment of a fully detailed document by parsing a document into a plurality of lines in an outline form and assigning a hierarchy to each line. Values or weights are determined for each of a relatively small plurality of key words in accordance with the key word and the hierarchy level of the line in the parsed document in which the key word is found. An adjustment is made based on a category of the key word such as nouns and verbs and the hierarchy level of the lines as compared with the number of hierarchy levels found in the document. Further adjustments may be made for subject matter domain of the product and the source or author of the document.

The invention, which belongs to the airborne LiDAR ground point cloud data classification field, discloses a virtual-seed-point-based airborne LiDAR ground point cloud filter method. The method comprises: grid transformation is carried out on an airborne LiDAR ground point and ground virtual seed points are constructed by using distribution dimensionality of point clouds in a grid and an elevation distribution histogram; virtual seed point evaluation is carried out by using the multi-scale morphology, a virtual seed point does not belong to the ground is rejected, and preliminary filtering is carried out on the point cloud; and an initial TIN network is constructed by using the evaluated virtual seed point and iterative encryption is carried out on the TIN network to complete ground point cloud filtering of LiDAR data. Therefore, the time spent in the filter algorithm is reduced and the filter precision of the filter algorithm is guaranteed; and the application range is wide.

The invention provides a self-focusing method and device of electronic camera, which finds the maximum evaluation value of being shot image. The maximum evaluation is high frequency component, which is optimum focusing point evaluation value. The invention moves at non-fixing steps activation motor, which needn't move motor reciprocally.

The invention provides a point of interest recommendation method for fusing social network and image conten.Based on the existing social recommendation model, a new matrix decomposition model which integrates social network and image content is proposed, which can make full use of the picture information in user evaluation information, alleviate the sparsity of data, and improve the accuracy of interest point recommendation. In addition, the invention utilizes the text information, the geographic information and the tag classification information of the interest point evaluation to better solve the cold start and accuracy problems of the interest point recommendation, recommends the most desired interest point to the user, and improves the user's experience degree.

Provided is a method for acquiring map interest point evaluation data. First, user released content on a third-party network platform is acquired, the user released content and an interest point are correlated, the user released content relevant with the interest point is acquired, then, the correlated user released content is processed, and the user released content matched with the interest point is acquired. Due to the fact that the third-party network platform has the needed evaluation data, the evaluation data matched with the interest point can be selected by automatic correlating and processing, an operator does not need to collect feedback information, and a user does not need to login to carry out evaluation on a certain interest point. Therefore, the map interest point evaluation data can be easily and conveniently acquired through the method and a device, and in addition, the invention further provides the device for acquiring the map interest point evaluation data.

A method and system for adjudicating measurement data in real time and re-adjudicating a segment of an input measurement data stream upon submission of a new adjudication instruction in a service level evaluation system. An adjudication instruction associated with a service level is received. Measurement data including a first measurement data point is received. The received adjudication instruction is applied in real time to the first measurement data point to generate a first adjudicated measurement data point. A service level is evaluated based on the first adjudicated measurement data point. To re-adjudicate the data stream segment, a new adjudication instruction is received and the segment is identified. The input data stream's adjudication is suspended and the stream is queued into storage. The segment of measurement data is retrieved and re-adjudicated by applying the new adjudication instruction. The input data stream's adjudication is resumed afterwards from the queued input stream.

The invention discloses a volume fracturing method for greatly improving the filling efficiency of a micro-support system through deep shale gas. The volume fracturing method comprises (1) deep shalekey parameter evaluation; (2) geotechnical engineering comprehensive sweet point evaluation and section cluster perforation position determination; (3) crack parameter system optimization; (4) fracturing construction parameter optimization; (5) different-viscosity smooth water and smooth water, carbon dioxide foam fracturing fluid and pretreatment acid solution formula optimization; (6) perforation operation; (7) acid pretreatment; (8) supercritical carbon dioxide multi-scale crack construction; (9) low-viscosity smooth water branch crack and micro crack expanding and main crack producing construction; (10) alternative injection through supercritical carbon dioxide and smooth water; (11) smooth water and carbon dioxide foam fracturing fluid small particle size supporting agent injection; and (12) displacement operation. By means of the volume fracturing method, the net pressure of a main crack can be improved to the greatest extent, the width of a multi-scale crack is expanded, the flow guiding capability is improved, and therefore the purpose of improving the deep shale gas fracturing effect and increasing the yield is achieved.

The invention discloses a voice command detection model constructing method. The method includes determining a typological structure of a voice command detection model; collecting a large amount of man-machine interaction voice data and recognition texts corresponding to the voice data; performing word segmentation on sentence texts of user questions or answers in the recognition text and acquiring word segmentation word strings in the unit of a single-round answers or questions; performing voice command end point evaluation on words in the word segment word string in sequence according to dialogue history information, and marking service types and an information slot or a state slot; by utilizing the recognition text and the evaluation information and mark information of the recognition text, performing training and acquiring parameters of the voice command detection model. The invention also discloses a voice command detection method and system, and a man-machine interaction method and device. The invention can improve voice command point detection accuracy and therefore improves success rate and response speed of machine response in a man-machine interaction process.

The present invention includes: a reel display module that changingly displays multiple types of symbols in multiple regions and also statically displays these changingly displayed symbols in these regions; measuring modules for measuring or storing modules for storing the number of times a special symbol, which is a symbol selected out of these symbols, is displayed in a changing manner and / or a static manner; and a game points evaluation module determining game points to be awarded to the player. The present invention increases a player's curiosity and anticipation for a game.

The presented invention is an apparatus for human identification; registration; and protection executed in combination by a mobile device and a computer comprising: a mobile device consisting of a camera for capturing and recording video and audio data; a server for receiving video streamed to it by the mobile device for sign-up or sign-in; working from a computer or mobile device and using an Internet connection; accessing an authentication unit. The authentication unit creating data for registration. The authentication unit also creating identification data; and sending to verification; a match combined with 9 out of 17 positive point evaluations returns, via an Internet connection to the mobile device.

Data acquisition and automatic diagnosis is performed at test points by respective wireless monitoring units (WMU). Each WMU tests a first indicator periodically at a first rate to determine whether to test a full set of indicators. Evolution of the first indicator determines the pass / fail result of a reduced assessment of the corresponding test point. The pass / fail result is automatically sent off-site to a central database. When a fail occurs, a full assessment is performed, which includes monitoring the full set of indicators. Automatic diagnosis is performed based on the full set of indicators. The reduced assessment does not include automatic diagnosis of a test point, but is used to decide whether to perform the full assessment and automatic diagnosis. Results of the automatic diagnosis are sent to the central database. Raw data is not sent automatically.

The invention belongs to the field of electric power system planning, and particularly relates to an extra-high voltage drop point plan optimal selection method based on a cloud model. The method includes the steps that (1), an extra-high voltage drop point evaluation index system about safety, regional characteristics and perspective adaptability of drop points is set up; (2), an evaluation index weighting method based on a variance maximization model is set up; (3), the extra-high voltage drop point plan optimal selection comprehensive evaluation method based on the cloud model is set up. The requirement for the complete, comprehensive and effective evaluation index system for evaluating the extra-high voltage drop points is met, an effective tool is supplied to eliminate the influence on determination of evaluation index weights by using the single weighting method, and a reference basis is provided for adding the new extra-high voltage drop point plan optimal selection method and applying the cloud model to comprehensive evaluation of extra-high voltage drop point plan optimal selection.

The invention discloses an internet teaching auxiliary teaching system based on the key teaching point evaluation. The system comprises a student terminal image collection device which collects a face image of an evaluated student; an information transmission device used for transmitting the face image acquired by the student terminal image acquisition device to the classroom behavior analysis processor; a class behavior analysis processor used for classifying emotions of the students when learning a plurality of knowledge points related to the key teaching points and respectively endowing the emotions with mastering probability values; an intelligent classroom device used for realizing teaching interaction with the student terminal, and automatically judging whether the corresponding knowledge points are mastered or not according to the correct and wrong conditions of all questions in the teaching interaction; and a key teaching point evaluation device which calculates the total mastery rate of the key teaching points according to the analysis and judgment results of the classroom behavior analysis processor and the intelligent classroom device. According to the system, related videos of the key teaching points can be conveniently and quickly found according to the mastery condition of the key teaching points. The course look-back is effectively carried out based on recording and playing courses.

The invention relates to a structured light stripe central point reliability evaluation method. An evaluation object is a light stripe central point obtained from a light stripe image by adopting a method, and structured light stripe central point evaluation basis is energy sum of a Gauss normalization model which takes the central point as the center on the cross section in the normal direction of the light stripe. The method includes: a light stripe central point is extracted by adopting a method, a point sequence of cross section in the normal direction of light stripe at the central point is acquired, and Gauss model normalization is carried out on the point sequence of the cross direction in the normal direction of the light stripe; energy sum of normalization Gauss model of the point sequence of cross section in the normal direction of the light stripe is calculated, and reliability evaluation index of the point is obtained; grey scale sum of the calculated light stripe central point cross section normalization Gauss model sequence is calculated; normalization of global image is carried out on the obtained central point reliability evaluation index, reliability is normalized according to reliability maximum of the image, and finally normalized reliability evaluation is obtained. The evaluation on light stripe central point in the invention accords with actual evaluation requirement.

An apparatus for connecting a human key identification to objects and content or identification, tracking, delivery, advertising, and marketing. An Independent Clearing House Agent (ICHA) server is connected to a human key server. The human key server is connected to a translation server and universal virtual world (UVW) server for the management of a plurality of methods and mechanism integrally working as one system. A virtual world airport (VWA) server is connected to a Mobile, Handheld, and Independent Device Application Development (MHIDAD) server which in turn communicates with an illumination transformer audio video manager interactive server transmitter (ITAVMIST which communicates with a Virtual Cash Virtual Currency (VCVC) server. The authentication unit also creating identification data; and sending to verification; a match combined with 9 out of 17 positive point evaluations returns, via an Internet connection to the mobile device.

The present invention relates to a photovoltaic array state determination method. The method comprises: collecting feature parameters that affect each photovoltaic array state; introducing a time sequence node and a photovoltaic array monitoring point, and establishing a parametric value model from latitudinal and longitudinal dimensions; constructing a photovoltaic array running state assessment model based on a positive and negative ideal point assessment scheme; and establishing a time function relationship between a state assessment result set and each longitudinal and latitudinal parametric value by using a Gaussian curve fitting method, and in combination with an array I-V curve and an irradiance-temperature curve, accurately assessing a current photovoltaic array state from longitudinal and latitudinal angles, analyzing an abnormality cause, and proposing an operation and maintenance measure. By performing state assessment according to a plurality aspects of feature parameters, accuracy of state assessment can be improved, real-time operation and maintenance of a photovoltaic array is facilitated, and the method lays a good foundation for improving power generation efficiency of a photovoltaic array group and searching for a better MPPT algorithm and has high application value.

The invention discloses a personalized line recommendation system and method based on a position social network, and belongs to the technical field of information. The invention aims to solve the problem that the matching degree of information such as offline mining of interest points and stay time, expenditure and the like of a server and the willingness degree of a user needs to be further improved in the existing line recommendation method and the problem that the travel efficiency of a recommended line is low. The system comprises an offline interest point planning module which acquires interest point information according to user history sign-in data and carries out clustering according to the interest point information; An interest point evaluation module which constructs an interestpoint scoring model based on user and time characteristics according to the obtained interest point information and carries out scoring; The planning request module is used for acquiring user input information and generating a route planning request; And the route planning module plans a route according to the interest point information of the user, the user information module, the starting placeinformation and the starting time information. The method is suitable for personalized line recommendation.

The invention discloses a shared automobile parking network point determining method based on automobile using behaviors in the field of shared trips. The method comprises the following steps: acquiring GPS position data of each vehicle during temporary parking from a vehicle management system; obtaining parking network points within a set range of the GPS position data and taking the parking network points as candidate parking network points; hierarchical analysis, setting weights for all the first-level indexes of the candidate parking network points respectively, and calculating scores of all the first-level indexes; according to the weight and the score of each first-level index, obtaining a second-level index; calculating a comprehensive score of each candidate parking network point; inputting the comprehensive score into a pre-created parking network point evaluation model; acquiring, the grade of each parking network point in the candidate parking network points generating the grade list and selecting a certain number of parking network points from the candidate parking network points as the parking network points according to the grade list, so that the site selection of the supplementary parking network points in the later period is effectively realized, the user consumption experience is improved, and the urban traffic resource configuration is optimized.

The invention relates to an evaluating method for a container energy storage equipment core part based on remote monitoring. The method comprises the following steps: establishing a standard curve view of single battery data under standard feature points; acquiring actual feature point data of a single battery in real time by a remote server, and establishing an actual curve view of battery data of the single battery under the actual feature point data; comparing the actual curve view of battery data of the same feature point with the standard curve view of battery data for analysis; weighting analyzed data, so as to obtain feature point evaluation value of the single battery; according to the feature point evaluation value and a feature point weight determined by a practical situation, obtaining the project evaluation value of each single battery through computation. According to the invention, the evaluating method has the technical benefits that the scientific selection of the core part is realized, the method is more scientific, objective and accurate, and the time cost and economic cost are reduced.

A hybrid learning system is provided for searching an experimental space. A data mart is configured to acquire, store, and manipulate a set or meta-set of data including at least historical experimental data, descriptor data, and concurrent experimental data. A search engine is designed to use unsupervised learning techniques to select a set of evaluation points representing a corresponding set of experiments to be run, based on data from the data mart. A point evaluation mechanism provided with supervised learning modules which perform predictive processing based on the evaluation points selected by the search engine, and a scoring module performs a rating operation on outputs of the learning modules to rate the outputs of the learning modules from best to worst. The data mart search engine and point evaluation mechanism allow for a repetitive processing to refine an output of potential solutions without the requirement of continually running actual physical experiments.

An embodiment of the invention provides a region delineation method and system. The method comprises steps as follows: acquiring a to-be-analyzed image of a study region, and pre-processing the to-be-analyzed image; establishing an analysis document, and analyzing the pre-processed to-be-analyzed image according to the analysis document to mark element points in the to-be-analyzed image; establishing an evaluation index, and obtaining evaluation results of blocks contained in the to-be-analyzed image according to the evaluation index and mark results of the element points in the to-be-analyzedimage; performing region delineation according to the evaluation results of the blocks in the to-be-analyzed image; generating corresponding databases and data tables according to image information of the blocks contained in the delineated region. According to the region delineation method, the region meeting the need is obtained by adopting modes of element point mark, element point evaluation and block evaluation, and compared with traditional survey methods, the method has advantages that the processing is more convenient and the result is more reliable.

The invention discloses a network security decision-making method and device for a game attack and defense graph and a storage medium, and the method comprises the following steps: employing an optimal vulnerability evaluation weight combination search algorithm and an optimal vulnerability point evaluation weight combination selection algorithm to evaluate vulnerability points of all host nodes,and obtaining high-diversity scores of the vulnerability points; constructing a state attack and defense graph; calculating the success probability and hazard index of attack accumulation in the stateattack and defense graph in combination with the high diversity score of the vulnerability; establishing a game model according to the state attack and defense graph; solving the game model to obtainan optimal attack and defense strategy. An optimal vulnerability evaluation weight combination search algorithm and an optimal vulnerability point evaluation weight combination selection algorithm are adopted to evaluate vulnerability points in a target network, the actual harm condition of each fragile point can be effectively distinguished, so that a more reliable game attack and defense graphis established, the optimal security strategy of the network is obtained by solving the game attack and defense graph, and the network management of the maximum income is realized.

The invention discloses a hypertension auxiliary diagnosis method, which comprises the steps: generating a knowledge base and association rules, and automatically generating a patient database based on the knowledge base and the association rules; based on data before diagnosis and treatment of a patient to be diagnosed and treated, selecting k similar records from the data before diagnosis and treatment of a plurality of patients in the database; based on the selected k similar records, carrying out clustering by utilizing k records corresponding to the k similar records in diagnosis and treatment scheme data in the database; and based on the clustering result, establishing a scheme model with a preset diagnosis and treatment end point evaluation index by utilizing the data after diagnosis and treatment in the database. The invention further discloses a hypertension auxiliary diagnosis system corresponding to the method. Due to the fact that the individual characteristics of hypertension patients are greatly different, and blood pressure reduction schemes are complex, for recommended similar patient re-clustering scheme recommendation, more accurate crowd positioning can be achieved to assist doctors to make diagnosis and treatment scheme precision and personalized decisions.

The present invention provides a noise point changing determination method and device. The method comprises: dividing an object image into a plurality of areas; determining the noise point evaluation area in the areas according to the average brightness of pixels in each area and the brightness variance of each pixel in the areas; performing the statistics of the brightness variance of each pixel in the noise point evaluation area; and determining whether noise point changing of the object image occurs according to the brightness variance of each pixel in the noise point evaluation area and the image sensor gain of the noise point evaluation area, and outputting a determination result. According to the embodiment of the invention, the accuracy of the determination of the noise point changing may be improved.

The invention relates to the field of data analysis, and discloses a user interest point evaluation method, a device, a computer device and a storage medium. The method comprises steps of acquiring position data of a user; Determining a target area range according to the position data; Acquiring a preset point of interest discrimination model associated with the target region range; Acquiring a processing rule associated with the preset point of interest discrimination model; Processing the position data according to the processing rule to generate position input data; The position input datais inputted into the preset interest point discrimination model to obtain an interest point discrimination result of the position data, and the user's interest point is determined according to the interest point discrimination result. The invention processes the position data of a user through a preset point of interest discrimination model to obtain the point of interest data of the user, which can obtain the point of interest of the user based on the sparse position data of the user without increasing the input of the position acquisition device, and judge the geographical position preference of the user.

The invention relates to a method and system for quantitative analysis of knowledge point. Wherein the system includes a first knowledge point weight setting module for setting a weight of each knowledge point occupying the content of the test question, A second knowledge point weight setting module for setting the source weight of each knowledge point, a knowledge point standard score calculationmodule for calculating the standard scores of each knowledge point, and a knowledge point evaluation score calculation module for calculating the knowledge point mastery situation of the evaluation students. By setting the weight of knowledge points and combining the students' problem-solving results, the standard scores of students' knowledge points are calculated, and then the scores of students' knowledge points evaluation are calculated, to obtain the analysis results objectively reflecting students' knowledge points, to assist educational management institutions, schools, teachers to improve the quality of teaching, so that students can better grasp the knowledge points.

The invention discloses an optimal distribution point evaluation method for substation area power quality management equipment. The method comprises steps of acquiring the characteristic parameters ofvarious load nodes on a substation area line; constructing an optimization model with an objective function of minimizing the active loss of the substation area; analyzing, based on the acquired characteristic parameters of the respective load nodes, the optimization model to obtain the to-be-compensated capacity required by each load node; and formulating a distribution plan of the power qualitymanagement equipment based on the to-be-compensated capacity required by each load node. The method can reasonably plan the power quality management equipment, reduces the power loss of the substation area, and maintains the three-phase load balance of the substation area power distribution system.

The invention relates to an automatic collaborative decision-making method for the professional authentication knowledge. Cooperative decision-making mechanisms of several kinds of evaluation means are provided. To be specific, mainly two kinds of mechanisms including an examination evaluation difficulty adjusting cooperation mechanism and a technical index point and non-technical index point evaluation cooperation mechanism are provided. The examination evaluation difficulty adjusting cooperation mechanism is based on initial examination evaluation T1 and employs curriculum group support evaluation T2, indirection evaluation T3, and space teaching method evaluation T4 as the adjusting evaluation means; and after the initial examination evaluation T1 is adjusted based on cooperation of the cooperative decision-making mechanisms of several kinds of evaluation means, thereby obtaining adjusted examination evaluation T5. According to the technical index point and non-technical index point evaluation cooperation mechanism, whether an index point is a technical index point or a non-technical index point is determined; and cooperation is carried out based on the curriculum group support evaluation T2, indirection evaluation T3, space teaching method evaluation T4, and adjusted examination evaluation T5, thereby obtaining a completion situation of the index point. iterative increment division is carried out and the knowledge is discovered in an iterative mode each time; and thus an opportunity is provided for evaluating the demand and the design again.

The invention discloses a unit online monitoring method based on big data, and the method comprises the steps: firstly enabling real-time data to be directly connected to a single-point evaluation model during monitoring, and quickly detecting the operation state of equipment or whether the data is noise through the single-point evaluation model; or when the single-point evaluation model judges that the equipment operates and the real-time data is non-noise data, the real-time data can be accessed to the abnormal data model, and the abnormal data model is established based on the abnormal historical data, so that when the real-time data and the abnormal data model are successfully matched, the system can quickly and accurately send out an equipment exception signal, so that a worker can check and overhaul an exceptional state, and the fault monitoring efficiency and accuracy of the monitoring system are improved.