735 results about "Single factor" patented technology

The invention provides a measuring method for an isothermal adsorption/desorption curve of coaly shale. The measuring method mainly comprises the following steps of: placing a coaly shale specimen into a true triaxial core clamping system; setting an initial measuring state of the specimen according to the actual stratigraphic condition; carrying out an adsorption/desorption experiment on the specimen after the volume of a free pore is calibrated; respectively measuring and recording a cumulative flow value of gas at an inlet end or outlet end and a balanced system pressure value according to a high-precise gas mass flow meter at the inlet end or outlet end and a system pressure sensor; calculating to obtain the volume of the absorbed gas; and then, drawing the isothermal adsorption/desorption curve of the coaly shale specimen. By using the measuring method, influences of a strain field, a temperature field and the like to the adsorption/desorption of gas on the surface of the coaly shale can be truly reflected, experiments carried out under the influence of single factor and experiments carried out under the coupled action of multiple factors can be achieved, and the measured adsorption/desorption curve can be used for truly representing the adsorption/desorption characteristic for gas in an actual coaly shale reservoir.

The invention relates to the technical field for evaluating the operation state of a transformer, in particular to a method for evaluating the operation state of a dry type transformer. Influences of parameters to the operation state of the dry type transformer are integrated, reliable level analysis is carried out on the operation state of the dry type transformer, and the convenience is brought for operators to hold the operation condition of the dry type transformer in real time and immediately make condition based maintenance. The method comprises the following steps of: 1) detecting parameter data of the operation state and an operation environment of the dry type transformer, and obtaining inherent characteristics of the dry type transformer and parameter data of the operation history; 2) normalizing parameter data of the operation states, the operation environment, the inherent characteristics and the operation history of the dry type transformer; 3) obtaining each parameter membership corresponding to a comment through a membership function of each parameter and the comment, and obtaining a single factor judge matrix; 4) obtaining a comprehensive judge matrix by combining weights of the parameters; and 5) obtaining a comprehensive evaluation value the operation state of the dry type transformer. The operation state of the dry type transformer can be reflected through the evaluation value.

The invention discloses a new method for predicating the residual life of a lithium-ion battery. The method comprises the following steps of sampling an experimental sample, and determining the rated capacity and rated internal resistance of a sample battery; respectively setting three influence factors, namely different ambient temperatures, discharge rates and discharge depth; measuring the increase rates of the internal resistance of the battery under influence of a single factor and two coupled factors, and establishing a correction factor database; determining three correction factors for the internal resistance of the battery by use of a curve fitting method; and collecting the constant-current charge time in real time, obtaining real-time variable battery internal resistance by use of the three correction factors and the rated internal resistance of the battery, and predicating the residual life of the battery by use of a Monte Carlo method. The method is capable of relatively accurately reflecting the variation trend of the battery capacity along with circulation times, and can also ensure the accuracy and rapidness of estimation on the residual life of lithium-ion batteries, and effectively guiding the reasonable use and maintenance work of the batteries.

The embodiment of the invention provides a database performance monitoring method, system and computer equipment as well as a computer readable storage medium. The method comprises the following steps: acquiring log data of a database and hardware information of a server in which the database is located; inputting the log data and the hardware information to a pre-warning monitoring module in realtime, wherein the pre-warning monitoring module outputs pre-warning monitored results of the database, and the pre-warning monitoring module adopts historical log data of the database and historicalhardware information of the server in which the database is located as input data. According to the scheme adopted by the invention, the log data of the database and the hardware information of the server are combined to monitor the state of the database, so that the problem that a false alarm rate caused by database monitoring through single factor is high is favorably avoided, the state of the database can be monitored more accurately, and the false alarm rate is reduced.

The invention discloses a method for evaluating a reservoir of a fractured well. The method comprises the following steps: S1, establishing an evaluation database M of the reservoir, wherein M is composed of a parameter set X, a sample set U and an index set Y; S2, dividing all the parameters into three kinds, and establishing a three-stage evaluation system including an index layer, an element layer and a target layer; S3, calculating the correlation between each parameter and open-flow capacity in the sample set U, and establishing a single-factor evaluation criterion set V; S4, calculating the influence weight W of each parameter to fracture improvement effect and the influence weight K of each kind of parameters to the fracture improvement effect in the sample set U by using a grey correlation method; S5, calculating and evaluating the membership degree R of each parameter in the object X in four different stages in the single-factor evaluation criterion set V by using normal-distribution membership functions; and S6, carrying out blurring operation on the weight W and the membership degree R, and grading quantifiably and comprehensively. The method for evaluating the reservoir of the fractured well, which is disclosed by the invention, has high objectivity and accuracy; a novel decision method is provided for selecting a fractured improvement well.

The invention discloses a simulation-based parameter optimizing method for a precise casting process of a single crystal turbine blade. According to the simulation-based parameter optimizing method, the technical problem of poor optimization effect of the precise casting process of the single crystal turbine blade is solved. The technical scheme provided by the invention is that the simulation-based parameter optimizing method comprises the following steps of: designing a casting system model of the single crystal turbine blade; carrying out unit division on the casting system model by adopting a finite element analysis method; obtaining a precise casting process parameter and a reasonable parameter change range which have greater influence on the dimensional precision of a precise casting blade molded surface by extracting and identifying precise casting process parameters through a single factor process test; carrying out numerical simulation on the casting process according to the established test table; estimating the deformation condition of a casting relative to the designed model by processing and analyzing the data; and gradually narrowing the search range of the parameter optimization of the precise casting process by establishing a BP (Back propagation) neural network model and adopting a small-step searching method. The optimization effect of the parameter optimization method for the precise casting process of the single crystal turbine blade is improved.

The invention discloses an urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof. The method emphasizes at modification research for failure states due to main factors such as corrosion, design, operation management, environments and third-party damage causing pipeline failure, a Bayesian network probability calculation model for a natural gas pipeline is established, single-factor multi-mode, two-factor multi-mode and multi-factor multi-mode situations of pipeline failure are respectively and quantitatively calculated, and pipeline failure tip event probability and structural importance of basic factors are obtained. By the method, the unique reasoning capability of a Bayesian network in complicated risk treatment system analysis is made full use of, comprehensiveness, predictability and systematicness of quantitative analysis of safety failure of an urban natural gas pipeline are improved, and a certain referential meaning for risk management and failure handling of the natural gas pipeline is achieved.

The invention provides a human-machine-environment comprehensive simulating test system for a special vehicle. The system comprises a test chamber, a control center, a six-freedom movement unit, a temperature/humidity control unit, an air pressure control unit, an air distribution unit, an occupant control unit, a vision scene unit, a sound unit, a chamber environment monitoring unit and a human engineering test unit, wherein the six-freedom movement unit, the temperature/humidity control unit, the air pressure control unit, the air distribution unit, the occupant control unit, the vision scene unit, the sound unit, the chamber environment monitoring unit and the human engineering test unit are connected with the control center. The test chamber is connected with the six-freedom movement unit. The test chamber is internally provided with the occupant control unit, the vision scene unit and the sound unit. The chamber environment monitoring unit and the human engineering testing unit are arranged at the positions which are next to the body of the occupant in the test chamber. The internal space of the test chamber is furthermore connected with the temperature/humidity control unit, the air pressure control unit and the air distribution unit so that an adjusting space for temperature, humidity, air pressure and harmful gases is formed in the test chamber. The human-machine-environment comprehensive simulating test system has a comprehensive testing capability and furthermore can more truly and effectively perform human-machine-environment comprehensive test research on a single factor and composite factors.

The present invention discloses a disease risk assessment and personalized health report generation system and method. The method comprises: inputting longitudinal health examination big data; arranging the data; defining the threshold range of various indicators of the disease according to the name of the disease, and using the sas software to establish a corresponding disease queue according to the threshold range of various indicators of the disease; and after establishing the queue, using the cox single factor regression analysis method to carry out variable selection on each variable; carrying out multi-factor regression analysis on the variables incorporated into the cox regression model; establishing a cox proportional risk model; verifying the inside of the cox proportional risk mode, and verifying the outside of the cox proportional risk model; obtaining a disease prediction model; generating a disease risk assessment hyperbola; inputting new individual physical examination indicators, generating disease risk assessment results according to the disease prediction model and the disease risk assessment hyperbola, and outputting a disease risk assessment and personalized health report according to the preset indicators.

The invention discloses a liquid drop wall hitting experiment device and a method. The device comprises a liquid drop injection system, a heating system, a visualized system and a signal control system. The experiment device and the method can effectively control the factors influencing the wall hitting of the liquid drop such as the size, the type, the wall hitting angle and the wall surface temperature so as to probe the influence of the change of the single factors on the liquid drop wall hitting, to conveniently explore the mechanism for liquid drop wall hitting and to search the method to increase the economy of the motor and suppress the super explosion.

The invention discloses a risk assessment method for an underground oil and gas pipeline. The risk assessment method comprises the following steps: A, determining a factor set which affects the pipeline risk assessment; B, determining a pipeline risk assessment alternative set according to assessment requirement; C, calculating the weight of each factor in the pipeline risk factor set by adopting a entropy weight method; D, calculating the weight of each factor in the pipeline risk factor set by adopting a combination analytic hierarchy process, and integrating the weights calculated in the step C into the calculation process of the analytic hierarchy process so as to obtain a final weight for each factor; E, performing fuzzy evaluation on single factors of pipeline risks by utilizing the weights obtained in the step D; F, iterating the calculation process of the step E so as to realize multilevel fuzzy comprehensive assessment on the risk of the underground oil and gas pipeline. By adopting the method, the problem that the weights of the factors of the risk of the pipeline are too objective or too subjective is avoided, and the calculated weight of each factor is more subjective and accurate; meanwhile, the risk of the underground oil and gas pipeline is assessed by establishing a fuzzy comprehensive assessment model, so that the assessment result is more accurate, subjective and reasonable.

The present invention relates to an encryption method based on biometric information. The encryption method provides a dual-factor encryption method based on the biometric information and the secret key, and a single-factor encryption method based on the biometric information. And the encryption method can be used in the fields of network and information security, bio-certification, biometric encryption, and so on. The dual-factor encryption and decryption of the information by the user both require the biometric information and the secure secret key or password which is automatically selected; if either of the biometric information and the secure secret key is not correct, the correct plaintext information can not be decrypted. The single-factor encryption and decryption of the information by the user only requires the biometric information. The encryption method can prevent the non-intended message recipient from decrypting the information; the attacker who obtains the decryption key of the other people can not complete the correct decryption process; the decryption process and the physical identity verification are completed simultaneously; the legitimacy of the identity of the decrypting person is verified; and the system has higher security.

The invention discloses a method for detecting the pollution grade of an insultor, which is characterized by comprising the steps of: 1. obtaining ultraviolet discharge pulse x1<0>, temperature valuex3<0> and humidity value x4<0>, and obtaining weather conditions; 2. determining the value of each parameter after normalization; 3. determining the constant weight value of each index factor; 4. obtaining the variable weight value of each index facor; 5. generating the membership function lists of discharge pulse and running age limit, and the membership function lists of the temperature value, the humidity value and the weather conditions; 6. generating the single factor judgement matrix A and matrix B of the index layer under intrinsic factors and enviromental factors; 7. obtaining the evaluating matrix S of the intrinsic factors; 8. obtaining the evaluating matrix Z of the enviromental facors Z; and 9. obtaining the status evaluation v of the insulator. The method has the obvious effects of: replacing the traditional method of climbing the rod for examination by workers and realizing continuous real-time detection. The method effectively conducts accurate and reliable grade analysis to the current running state of the insulator, and is convenient for monitoring and changing the insulator reasonably by the workers.

The invention relates to the technical field of well logging and discloses a water flooded layer well logging evaluation method and system. Sample values of at least two water flooding strength evaluation indexes of the same water flooded layer in a same petroleum well are acquired, weight analysis is performed on the sample values of the water flooding strength evaluation indexes, the weights of the water flooding strength evaluation indexes are acquired, according to the weights of the water flooding strength evaluation indexes, the sample values of the water flooding strength evaluation indexes are subjected to weighing calculation to obtain water flooding indexes of the water flooded layer, and thus the water flooding strength of the water flooded layer in the petroleum well is determined, and the accuracy of well logging evaluation of the water flooded layer is improved. Errors caused by a single-factor evaluation method are avoided.

The invention discloses a method for tuning and optimizing parameters of a dynamic absorber based on a machining process, which comprises the following steps: firstly, establishing a mathematical model of two degrees of freedom of a vibration system, and then solving the amplitude of the steady-state solution of a dynamics differential equation; taking the relative displacements of a main structure and the dynamic absorber in the viscous damping energy consumption formula; drawing an energy curve, and then making a statistics of the relation between a single factor vibration and the energy peak value; according to the statistics data, fitting the optimal frequency ratio and the optimal damping ratio corresponding to each mass ratio; according to the frequency range of an external disturbance signal, performing integration on the energy that the dynamic absorber can absorb; then, drawing an energy histogram and finding the maximum value so as to obtain the optimal mass ratio; finally, obtaining all optimal parameters of the dynamic absorber. With adoption of the method disclosed by the invention, the vibration caused by external disturbance can be restrained, so that the response speed can be improved by about 50%.

The invention discloses an image fusion effect evaluation method based on a convolutional neural network, wherein the method belongs to the field of image splicing and image quality evaluation technology and relates to the field of computer vision. The method comprises the following steps of S1, generating a training data set and a testing data set; S2, generating a convolutional neural network model; and S3, testing the testing data set based on the trained convolutional neural network. According to the image fusion effect evaluation method, the convolutional neural network can be used for replacing a large amount of complicated artificial statistics and scoring, and furthermore the fusion effect in image splicing can be accurately determined, thereby overcoming restriction caused by a single factor evaluation index, facilitating realization of a full-automatic adaptive image splicing system and realizing high application value.

A user network station transmits a cookie including a user identifier and an augmenting factor transformed with one key of a first asymmetric crypto-key or with a symmetric crypto-key. A authenticating entity network station recovers the augmenting factor from the transformed augmenting factor with the other key of the first asymmetric crypto-key or with the symmetric crypto-key, and transmits a customized login page corresponding to the user identifier included in the received cookie. The user network station transmits a factor responsive to the transmitted customized login page. The authenticating entity network station generates a first key portion based on the transmitted factor, and validates the generated first key portion based on a second key portion of one key of a second asymmetric crypto-key associated with the user and on the other key of the second asymmetric crypto-key, and the recovered augmenting factor, to thereby authenticate the user.

The invention discloses a method for predicting and simulating errors of an end-milled surface. The method includes the steps that various influence factors causing the machining deformation errors in the end-milling cutting process are analyzed, and a machined-surface single-factor and multi-factor error vector model and an error accumulation vector relation model are built in cooperation with end-milling characteristics; by virtue of a calculation and simulated analysis method, based on a solving method for the machined-surface flatness errors, according to a least regional method, the flatness errors are calculated with a self-adaptation genetic algorithm based on real number encoding, verification is carried out through living example calculation, and contrastive analysis is carried out on the errors and errors of a traditional genetic algorithm. The method is simple and convenient to operate, and the problems that heat stress is caused by cutting heat, residual stress is caused by unloading and loading loads, strict quantitative or logical relationships do not exist between the heat stress and the residual stress, and great difficulty is brought to analysis of the machined surface errors are well solved.

The invention provides a direct broadcasting room recommendation method and system. According to the method, on the basis of considering the number of direct broadcasting rooms viewed by different users, the correlation degree of different direct broadcasting rooms is calculated, and the direct broadcasting rooms are recommended according to the correlation degree of the direct broadcasting rooms.By adoption of the direct broadcasting room recommendation method and system, the similarity between the direct broadcasting rooms can be accurately measured so as to accurately and effectively recommend the direct broadcasting rooms; and the direct broadcasting room recommendation method and system have the beneficial effects of solving the problem that single factors are considered in the similarity measurement caused by the exiting related algorithms in the existing direct broadcasting room recommendation technical scheme.

The invention discloses a method for evaluating clarity of a stitched image, belongs to the technical field of image stitching and image quality evaluation, and relates to the field of computer vision. The method includes the following steps: S1. generating a training data set and a test data set; S2. generating a convolution neural network model; and S3. training the test data set on the basis of the trained convolution neural network. According to the invention, the method, based on an output label of each block output by the convolution neural network, computes the average value of the output labels of all the blocks which constitute a to-be-evaluated stitched image, then computing the average value of the output labels of all stitched images which are synthesized with the same stitching algorithm, the average value of the output labels of all the stitched images serving as a criterion for evaluating the effects of the stitching algorithm. The method, by means of the convolution neural network, can replace tedious and bulk amount of manual statistics and scoring, can accurately determine the clarity of a fusion region in stitching images, overcomes the limitation brought by single-factor evaluation index, can help the realization of automatic and self-adaptive image stitching system, and has significant application value.

The present invention provides a real estate evaluation method with multi-model integration, which includes the following steps: determining the real estate price influencing factor; constructing a real estate transaction case database according to the determined real estate price influencing factor; obtaining real estate transaction cases in relevant areas through the real estate to be evaluated; screening the real estate data to obtain comparable transaction cases; quantify the housing price impact factors and calculate the weights of housing price impact factors; use set pair analysis model, VIKOR model, fuzzy mathematical model, and neural network model to calculate relevant parameters respectively; correct the time of real estate transaction cases, and estimate Property prices to be appraised. The present invention adopts spatial information technology to establish a real estate database, and based on this, constructs a precise quantification method for real estate valuation factors and a batch evaluation mode for real estate prices fused with multiple mathematical models, which overcomes the subjective nature of price influencing factors in traditional single-model valuation methods The problem of uniqueness and the singleness of the valuation model.

The invention discloses a comprehensive evaluation method of water quality based on a water pollution index method and cloud models, and relates to an improvement on the water pollution index method by using the cloud models based on the water pollution index method. The cloud models are combined with WPI values in the water pollution index method, a WPI value evaluation cloud model is obtained by a cloud parameter determination method, a single factor WPI value cloud model is obtained by a backward cloud generator, a normal cloud generator is used to generate a WPI value evaluation cloud picture and a single factor WPI value cloud picture to intuitively see the pollution status of each single factor; weights are combined, a comprehensive WPI value cloud model is obtained through a comprehensive cloud algorithm, and comprehensive evaluation grades of the water quality are intuitively displayed by a form of cloud droplets and determined, so that the problems that contributions of all pollution factors in comprehensive evaluation of the water quality are not considered in the water pollution index method and comparisons among different sections are difficultly realized are effectively solved.

The invention discloses a small-sized comprehensive simulation system of lunar environment, which mainly comprises a vacuum system, a heat circulating system, a lunar dust simulating system, a radiation environment simulating system and a monitoring system. By adopting the vacuum system, the problem that a vacuum pump is damaged by a lunar dust simulated article in the vacuum-pumping and vacuum-keeping process is solved and the service life of the vacuum system is prolonged; and by adopting the lunar dust simulation system, the simulation problem of a lunar dust environment on a lunar surfaceis solved. The system integrates simulation abilities of multiple environment factors like high and low temperature circulation, lunar dust, vacuum ultraviolet, electronic radiation and the like in one vacuum chamber, and can be used for carrying out a simulation test on a single factor and comprehensive simulation test on the multiple factors. By using the invention, comprehensiveness and reliability of a lunar environment simulation test are increased and efficiency of a space environment simulation test also can be improved.

The invention provides a deep learning-based human face identification method for a real scene, which is proposed for solving the problem that an existing human face identification method for the realscene only can eliminate influence of single factor and cannot eliminate influence of factors of pose, illumination and the like. The method comprises the steps of predicting human face positions ofimages in a training database by using an existing human face detector, and capturing and storing real human face and non human face images; according to the human face images and the non human face images, performing down-sampling to obtain corresponding low-resolution images; building a generative adversarial network, wherein the generative adversarial network comprises a generator and an identifier, and the generator further comprises an up-sampling network and an optimization network; training the generative adversarial network by using high-resolution human face and non human face imagesand the corresponding low-resolution human face and non human face images; and according to scores of the identifier to candidate human face regions obtained from the existing human face detector, marking the human face positions in the input images. The method is suitable for human face identification detection.

The invention discloses a rhamnolipid high-yielding bacterial strain, and applications thereof. The rhamnolipid high-yielding bacterial strain is named as pseudomonas aeruginosa KT1115, is preserved at China Center for Type Culture Collection, and the preservation number is CCTCC M 2016686. The rhamnolipid high-yielding bacterial strain is stable in hereditary features and high in rhamnolipid yield, and is obtained via ARTP induced mutation, blue gel plate screening, and secondary screening. According to fermentation broth of pseudomonas aeruginosa KT1115, liquid surface tension is reduced to 24.8mN/m<2>, and emulsification value is as high as 80%. Optimization of fermentation conditions including carbon source and nitrogen source single factors, cheap crude glycerine and swill-cooked dirty oil are taken as a composite carbon source, so that production cost is reduced greatly. The rhamnolipid yield of pseudomonas aeruginosa KT1115 is 50.7g/L, is increased by 18.1 times compared with that of a starting strain, conversion rate is 0.75g/g, and is relatively high. Application prospect of pseudomonas aeruginosa KT1115 in further industrialized application is promising.

The invention discloses a method for detecting panoramic image registration effects, belongs to the technical field of image stitching and image quality evaluation, and relates to the field of computer vision. The method includes the following steps: S1. generating a training data set and a test data set; S2. generating a convolution neural network model; and S3. training the test data set on the basis of the trained convolution neural network. According to the invention, the method, based on an output label of each block output by the convolution neural network, computes the average value of the output labels of all the blocks which constitute a to-be-evaluated stitched image, then computing the average value of the output labels of all stitched images which are synthesized with the same stitching algorithm, the average value of the output labels of all the stitched images serving as a criterion for evaluating the effects of the stitching algorithm. The method, by means of the convolution neural network, can replace tedious and bulk amount of manual statistics and scoring, can accurately determine the clarity of a fusion region in stitching images, overcomes the limitation brought by single-factor evaluation index, can help the realization of automatic and self-adaptive image stitching system, and has significant application value.