41 results about "Analysis factors" patented technology

The invention discloses a nowcasting method and system of a thunder cloud cluster based on the boundary recognition and tracer technique. The method performs the cloud cluster boundary recognition and topology process to establish the relationship between cloud cluster life timing and clan pedigree by using the pattern recognition technique. The method comprises the steps of performing the boundary recognition on the pre-processed radar data; respectively recognizing the life timing of each cloud cluster and the information of moving direction, velocity, area and strong center and the like ofeach cloud cluster through the six judging factors of the quadtree matching analysis factor, the overlap factor, the area factor, the circum-rectangle factor, the outline comprehensive factor and thelocal similarity determination factor; and performing linear extrapolation on the moving direction, velocity, area and the strength of the cloud cluster. The preliminary result indicates that the system and the method of the invention can realize better recognition and extrapolation forecast of the thunder cloud cluster.

Methods, machine-readable media, and devices for face image prioritization based on face quality analysis are described herein. For example, one or more embodiments include detecting a facial image in an image that has been acquired by a camera that monitors a scene, passing the facial image through a number of quality analysis filters that include a number of quality analysis factors, wherein processing complexity associated with the number of quality analysis factors increases consecutively, and submitting the facial image to a facial recognition program upon a determination that the facial image has passed the number of quality analysis filters.

The invention discloses a dynamic screening and comprehensive weight setting method for low-voltage transformer area line loss rate analysis indexes, including the following steps of: collecting and summarizing low-voltage transformer area line loss rate analysis indexes, and establishing a first-level index system of a low-voltage transformer area line loss rate; dynamically screening the first-level index system by a principal component analysis, screening out a low-dimensionality second-level index system of the low-voltage transformer area line loss rate, using the low-voltage transformer area line loss rate as a third-level index, and thereby obtaining the dynamic index system, including three levels, of the low-voltage transformer area line loss rate; working out the comprehensive weight of the second-level indexes to the third-level indexes in the dynamic index system by a step analysis-factor analysis method, and assessing the contribution rate of each second-level index to the low-voltage transformer area line loss rate according to the obtain comprehensive weight. According to the dynamic screening and comprehensive weight setting method provided by the invention, on the one hand, a reference base is provided for analyzing the low-voltage transformer area line loss rate by a power supply enterprise; in addition, the contribution rates of the indexes to the line loss rate are assessed, thus being conductive to assisting the power supply enterprise to perform targeted management and transformation to the low-voltage transformer area line loss rate.

The invention relates to a method for evaluating high-gloss coating surfaces by a fuzzy logic model. The method comprises the following steps: (1) selecting glossiness, haze and pebbling as analytical factors of comprehensive evaluation; (2) establishing a Mamdani fuzzy inference system model; (3) obtaining a fuzzy set of various parameters of the glossiness, the haze and the pebbling value; (4) obtaining a corresponding output value of the comprehensive evaluation and a corresponding fuzzy set; and (5) obtaining final comprehensive evaluation scores. The method has the following advantages: (1) flexible parameter selection and very good expandability of algorithm; (2) visual output results; and (3) being capable of easily comparing quality differences among different coatings according to a quantized coating surface comprehensive quality index, which has relatively positive effect in the coating field.

The invention provides an on-demand computing-based data analysis device and method for analysis factors. The on-demand computing-based data analysis device for the analysis factors comprises a configuration module, a data extraction module, an analysis factor computing module, a data analysis processing module and an analysis result output module. The on-demand computing-based data analysis device and method for the analysis factors, which are disclosed by the invention, have the advantages that the analysis factors and analysis rules are easy to expand, the timeliness and the accuracy can be guaranteed, the analysis factors can be computed on demand, and thereby the work efficiency and the performance of a system are markedly improved.

The invention, which relates to the operation maintenance field of the communication network, discloses a margin checking system for a power communication network. On the basis of a topological structure of a power optical communication system, an importance weight of a carrier power business is used as an analysis factor and main factors affecting reliability of optical transmission equipment and an optical fiber link are taken into consideration comprehensively; and the communication risk probability existing in the power business is analyzed to realize advanced early warning, automatic route optimization selection is carried out on a business channel with a communication risk, and prevention measures are taken to reduce the risk of interruption of the power business. The system mainly comprises a reliability evaluation model of a communication network and a risk evaluation algorithm of a business path. According to the invention, the scientific and effective analysis means is provided for network usability, so that the communication operation maintenance staff can find the communication network margin accurately; and the practicability is high.

The invention provides a fatigue detection method. The fatigue detection method includes: continuously acquiring face images of a personnel, and extracting characteristic point information of eyes and the mouth; respectively calculating closing proportions of the right eye and the left eye and the opening time of the mouth; and determining whether the calculated closing proportions of the right eye and the left eye are greater than a preset closing proportion threshold and determining whether the calculated opening time of the mouth is greater than a preset opening time threshold, determining the fact that the personnel is not in a fatigue state if the closing proportions of the right eye and the left eye and the opening time of the mouth are both not greater than the corresponding closing proportion threshold and the opening time threshold, and determining the fact that the personnel is in a fatigue state if one or more of the closing proportions of the right eye and the left eye and the opening time of the mouth is greater than the corresponding closing proportion threshold and the opening time threshold. According to the fatigue detection method, analysis factors are comprehensive, and the identification accuracy is high.

The invention relates to a method for analyzing general rearranging of transmission network based on relativity analysis of rearranging factors. The method includes the following steps: A. when the network element generates rearranging massages, all the rearranging factors generated recently are obtained to form a collection of factors to be analyzed. B. the rearranging factors resulted from Step A are filtrated according to time relativity. C. the rearranging factors resulted from Step B are filtrated according to space relativity. D. the rearranging factors resulted from Step C are filtrated according to business relativity and the unprotected rearranging factors in business are eliminated. E. the derivative factors and rearranging massages resulted from Step D are eliminated. F. the entity that generates root factors and that resulted from E is located on the object tree. G. the rearranging direction, the rearranging reason and the business view after rearranging are analyzed according to the protection type and the ending time of the rearranging factors. The method of the invention can, without considering equipment types, realize unified analysis of rearranging features and present the whole business rearranging view as well as the fault reasons that cause rearranging.

The invention discloses an online cigarette tar predicting and warning method. The method comprises the following steps: acquiring ingredients of cut tobaccos by using near-infrared light, determining critical factors of a tar prediction model, and composing analysis factors; carrying out weighted distribution on the analysis factors, and constructing the tar prediction model; determining a central value according to monitored values of the analysis factors, and calculating upper and lower control limits, so as to form warning threshold values. According to the method, the cigarette tar prediction model is constructed, so that the deviation of a cigarette tar prediction result is small; corresponding relationships between an optical spectrum and parameters to be measured are established by using an online near-infrared technology so as to determine chemical ingredients of the cut tobaccos, thus, the analysis speed is high, the non-destructivity and sample preparation are low, the method is almost applicable to all kinds of samples, and multicomponent and multichannel simultaneous determination is achieved.

The invention discloses a computer room energy efficiency optimization technology based on data simulation and dynamic environment linkage, and belongs to the field of computer room energy efficiency management. The computer room energy efficiency optimization technology based on data simulation and dynamic environment linkage is characterized in that the technology includes a data simulation link and a dynamic environment linkage link; the data center simulation technology takes an actual data center scene as a prototype, the CAD drawings of the computer rooms of a data center and data of the computer rooms are acquired, the data building, computer room building and equipment of the data center are simulated according to the actual condition by means of 3D modeling, and the scene is real and visual; and the dynamic environment linkage technology includes temperature and humidity dynamic environment linkage, UPS system dynamic environment linkage, computer room air conditioning linkage and cabinet linkage. According to the computer room energy efficiency optimization technology based on data simulation proposed by the invention, the simulated computer room temperature, air distribution and power loss are taken as analysis factors, and the main factors influencing the energy efficiency of computer rooms are considered comprehensively.

The invention discloses a model building system of a concrete continuous box girder bridge. The model building system comprises the specific steps that 1, comparison and selection are conducted on a bridge type building scheme, and a bridge construction scheme is drafted; step 2, drawing up the size of the upper structure of the bridge; 3, establishing a space finite element model of the bridge structure by applying midas civil software; 4, performing curve continuous box girder counter-force checking calculation, and continuously adjusting the structure size or reinforcing bars until all checking calculations meet the standard; 5, structural internal force calculation and internal force combination are carried out; the invention relates to the technical field of bridge construction. According to the model building system of the concrete continuous box girder bridge, the problems that an existing data simulation system is too tedious in process, large in error and incomplete in analysis factor are solved.

The invention provides a method for quickly identifying factors for analyzing a target pollutant source. The method comprises the following steps: collecting published documents related to the targetpollutant source analysis in contents; extracting graphs and data related to sources corresponding to target pollutant source analysis factors from the published documents, and constructing a trainingset and a test set for training learning to obtain a preliminary training model; verifying the training model by adopting a cross validation method based on an artificial neural network to obtain a final factor recognition model; analyzing a to-be-detected sample, and calculating unrecognized factors; calculating the unrecognized factors by using a factor recognition model, and analyzing a pollutant source corresponding to the factors. According to the method for quickly identifying PMF factors, a source corresponding to each factor is automatically identified by an artificial neural networkdeep learning algorithm, so that the factor identification speed and the factor identification accuracy are greatly improved. Meanwhile, the subjectivity of manual selection is avoided.

The present invention provides a DDoS detection method, which relates to the field of network intrusion detection. Aiming at the huge characteristics of the current DDoS attack traffic and the amplification attack of UDP data flow, it distinguishes the traditional DDoS detection that pays more attention to TCP, and utilizes the current Spark Streaming technology. The platform applies multi-measurement factors to quickly parallelize the analysis of time series streams obtained by stream sampling, and gives indicators of DDoS attacks. The present invention is based on the abnormality detection method of the current flow sampling, is also based on the business dynamics and advanced technology, has the characteristics of low delay detection, can effectively detect the current reflection amplification attack, and can detect the new type of DDoS. Compared with the prior art, the DDoS detection method based on flow sampling provided by the present invention has the following beneficial effects: scalable cloud detection framework; real-time low-latency detection based on Spark Streaming; adaptive detection of current emerging DDoS attacks Type; effectively detect the current reflection amplification attack.

The invention relates to the field of structural analysis of friction stir welding robots, in particular to a topological optimization design method for a base structure of a friction stir welding robot, which comprises the following steps: step 1, determining analysis factors; 2, dynamically and optimally designing the base to obtain a topological optimized structure of the base; 3, further optimizing the relation between the sand outlet holes of the rib grid units and the inherent frequency of the rib grid units; 4, further optimizing the relationship between the wall thickness and side length of a rib plate of the rib grid unit and the inherent frequency of the rib grid unit; 5, further optimizing the density of the rib grid units in the base, and determining the layer number of the ribgrid units and the size of a base frame; and 6, verifying the optimal scheme of the base structure. According to the method, through finite element analysis, the design variables sensitive to the optimization target of the base structure are found, a group of optimal solutions of the design variables in a specified multi-target weighted optimization algorithm are solved, and finally a reasonablescheme of structural design is given and used for improving the comprehensive dynamic performance of the base structure.

The invention relates to the technical field of data analysis, and discloses a data analysis device and an operation method, the data analysis device comprises a data analysis system, the interior ofthe data analysis system comprises a data source and a data processing module, and the output end of the data source is connected with a data extraction module, and the output end of the data extraction module is electrically connected with an analysis factor calculation module. Original data is transmitted to the interior of a data extraction module through a data source; the data extraction module is matched to further extract the original data; unavailable data in the original data are effectively prevented from entering a data analysis module; the screened data enters an analysis factor calculation module, and the data is sorted through a calculation unit; and a data analysis rule template setting unit in the data processing module is matched to further set an analysis rule for data analysis, and data is analyzed according to the data analysis rule set by the data analysis rule template setting unit.

The present invention provides an enterprise credit risk assessment method and an apparatus. The method comprises the steps of extracting an objective factor out of an objective circumstance survey report of a to-be-trusted enterprise, and adopting the objective factor of the objective circumstance survey report as a first objective factor; inputting the first objective factor into each pre-stored risk analysis model, and outputting a first analysis factor corresponding to each risk analysis model; inputting the first objective factor and the first analysis factor into each pre-stored risk judgment model and outputting a first conclusion factor corresponding to each risk judgment model; executing the operation till the outputted first conclusion factor does not change at all. The above operation comprises the steps of inputting the first objective factor, the first analysis factor and the first conclusion factor of the last output result into each pre-stored risk judgment model, outputting the first conclusion factor corresponding to each risk judgment model, and combining the first objective factor, the first analysis factor and all first conclusion factors to form a credit risk view.

The invention discloses a method for constructing evaluation indexes of human body heat acclimatization training effect. The method includes the steps: selecting five variables, such as heart rate, rectal temperature, eardrum temperature, thermal sensation, and RPE as the analysis factors; normalizing each variable, using SPSS software to carry out factor analysis, and selecting a factor with an initial eigenvalue greater than 1 as a common factor; and finally, performing linear analysis of the comprehensive index grading system. The method for constructing evaluation indexes of human body heat acclimatization training effect reflects the heat acclimatization training effect under different conditions through a unified index, and the method is simple and versatile.

The invention provides a data analysis device and a data analysis method based on dynamically expandable analysis factors. The data analysis device based on the dynamically expandable analysis factors comprises a configuration module, a data extraction module, an analysis factor calculation module, a data analysis and processing module and an analysis result output module. By the aid of the data analysis device and the data analysis method based on the dynamically expandable analysis factors, expansion is easy, instantaneity and accuracy can be guaranteed, and systematic operating efficiency and performance can be enhanced.

The invention discloses a method and a device for analyzing a reasonable value of a line loss benchmark of a power distribution network. The method comprises the steps of determining line loss data sample sets of a plurality of analysis dimensions based on equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network; performing system clustering analysis on the line loss data sample set under different analysis dimensions to form a reference clustering value scale; analyzing the line loss data sample set under differentanalysis dimensions by adopting a preset clustering algorithm based on the reference clustering value scale so as to select a target clustering value; determining a plurality of line loss reference domains based on the target clustering value, each line loss reference domain comprising a plurality of sub-analysis factors; and determining a line loss benchmark reasonable value corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference domains.

The invention relates to the technical field of Internet, in particular to a gray release method and device, a storage medium and electronic equipment. The method comprises the following steps: receiving a gray scale rule, wherein the gray scale rule comprises a gray scale analysis factor corresponding to a current rule version; obtaining a unique identifier of a service initiating terminal from the received service request; and determining a deployment environment to which the service initiating user belongs according to the gray analysis factor and the unique identifier, and segmenting the service initiating user to the deployment environment. According to the invention, the deployment environment of the service initiating terminal is determined according to the gray analysis factor in the gray rule and the unique identifier of the service initiating terminal, the user terminal can be timely adjusted to a reasonable deployment environment along with the change of the gray rule, and the gray effect is improved.

The invention relates to a management method of electrolytic aluminum, in particular to a management method of an electrolytic aluminum whole life cycle. The management method comprises the stages oftank building, roasting, starting, normal production operation and tank stopping. In the tank building stage, during construction, construction standards and technological requirements are set up forconstruction units, and construction information is managed and recorded; in the roasting stage, during roasting, material information, operation information and tank condition information of an electrolytic tank are recorded; and in the starting stage, during starting, operation parameters of the electrolytic tank are recorded and monitored. The management method has the advantages and effects that in the operation stage of the electrolytic tank, a mathematical model is built for the electrolytic tank, and analysis factors of several core parameters of the electrolytic tank are built correspondingly, so that the purposes of prolonging the life of the tank and improving the electrolytic production efficiency are achieved.

The invention discloses a main effect factor analysis method and equipment based on a causal model. The main effect factor analysis method based on the causal model comprises the following steps: constructing a Bayesian network model, and obtaining direct influence factors of a result node; obtaining an influence path set of influence of each direct influence factor on a result node; when the influence path set comprises indirect influence paths, analyzing the influence degree of the direct influence factors on the result nodes jointly based on the node interaction effect, and otherwise, calculating the influence degree of the direct influence factors on the result nodes directly by adopting an independent influence degree analysis method; and selecting the direct influence factor corresponding to the maximum value from all the influence degrees as a main effect factor. According to the method, the problem of factor isolation of a single-factor analysis method is solved, the main effect factor is extracted on the basis of fully analyzing the linkage interaction influence between the factors, and the reasonability and credibility of the main effect factor analysis conclusion are improved.

The invention discloses a flood staging determination method based on multiple characteristic indexes. The method comprises the following steps of dividing calculation time periods, selecting multi-feature indexes, constructing a projection index function, solving an optimal projection direction, calculating projection values of all the time periods and determining flood stages through ordered clustering. The method comprises the following steps: a projection index function is established by adopting a plurality of characteristic indexes capable of reflecting drainage and flood characteristics of a drainage basin on the basis of clearing the flood season duration of the drainage basin; then, through an accelerated genetic algorithm, a projection value which enables the projection index function to reach an optimal value is found, and through an ordered clustering analysis method, clustering analysis is carried out on the projection value; therefore, the flood staging is determined more objectively, and the defects of single analysis factor and subjective arbitrariness in a conventional analysis method are effectively avoided.

The invention discloses a network attack defense method, a server and a computer readable storage medium. According to the invention, feature information corresponding to a preset analysis factor is extracted from a service request initiated by a client based on the preset analysis factor in a pre-constructed behavior analysis statistical table, and the index data corresponding to the preset analysis factor is updated according to the extracted feature information, namely, the access behavior of the client to the website is mapped in the behavior analysis statistical table, so that a pluralityof target preset analysis factors meeting an attack judgment rule can be selected from the behavior analysis statistical table according to a preset attack judgment rule before the service request becomes a log; and whether the service request is an attack request or not is judged according to the attack judgment rule and the index data corresponding to the target preset analysis factor, so thatthe attack request is directly blocked, whether the service request is an attack behavior or not can be identified in advance based on the attack request, and the crawler attack identification, namelythe protection efficiency is greatly improved.

Systems and methods for additive manufacturing of vehicles are provided. An additive manufacturing apparatus can include a printer that additively manufactures structures for a vehicle, and multiple analysis components. Each analysis component can receive information based on a design model of the vehicle and analyze the information based on an analysis factor. Each analysis component analyzes theinformation based on a different analysis factor. An integrator can receives the analyzed information from the analysis components, update the design model based on the analyzed information, and determine whether the updated design model satisfies criteria. If the updated design model satisfies the criteria, the integrator determines printing instructions for the printer to print one or more structures of the vehicle based on the updated design model, and if the updated design model does not satisfy the criteria, the integrator sends information based on the updated design model to the analysis components.

The invention discloses a recognition method of molding traces of a car connector. The method comprises following steps: step 1, recognizing molding traces of an injection mold structure according to features of molding traces of the car connector; step 2, classifying molding traces of the injection mold structure according to a recognition result and finding out features and differences between different kinds of molding traces; step 3, determining concrete attributes of the injection mold structure. The recognition method of molding traces of the car connector provided by the invention is capable of accurately and rapidly finding out molding traces of the injection mold structure such that key analysis factors for improving the injection mold structure are provided.

The embodiment of the invention provides a data processing method, which comprises: through a plurality of preset penetration decomposition formulas, a transaction penetration rule and a plurality of analysis factors, performing penetration analysis on the plurality of analysis factors to obtain a plurality of intermediate data, constructing a fund virtual transaction as a first adjustment item, and constructing a cash virtual transaction as a second adjustment item; and according to the plurality of intermediate data, the first adjustment item and the second adjustment item, generating penetration data of the portfolio data, and performing visualization processing, the penetration data being used for representing income affiliation portfolio data of the portfolio data. According to the method, investment portfolio data is analyzed from multiple aspects of analysis factors such as share ratio data, multiple penetration decomposition modes, virtual transactions and cash flow data, so that the accuracy of data processing is ensured, the calculation amount of data is simplified, the processing efficiency of data is improved, and the operation burden of a CPU is reduced.