347results about How to "Improve evaluation accuracy" patented technology

The invention discloses an environment risk source pre-warning system, comprising a data collector, a data server, a risk real-time evaluation system and a warner. The data collector is used for collecting real-time monitoring data of detection points in an environment risk source. An environment risk source information database for recording environment risk source basic information and a threshold value database for recording the threshold values corresponding to the real-time monitoring data of the detection points are installed in the data server. The risk real-time evaluation system is used for carrying out security evaluation on the environment risk source and calculating the risk degree of the environment risk source. The warner is used for carrying out selective warning according to the risk degree of the environment risk source. According to the system, the risk evaluation and pre-warning can be carried out on the environment risk source, a monitor can be helped to take countermeasures effectively and timely, and losses resulting from a risk event can be reduced to the lowest.

The invention discloses a multistage load estimating method facing task scheduling of a cloud computing platform. The method provided by the invention fully considers dynamic variation of own loads of task nodes, difference in performance of different task nodes and difference in different task load needs, selects operation queue average progress number, average CPU (central processing unit) utilization ration, average memory utilization ratio and average network bandwidth utilization ratio as load parameters for estimating, and gives different priorities to load parameters, so that a multistage load estimating method is provided for task scheduling of a large-scale server cluster. An adaptive task scheduling method of the cloud computing platform further is disclosed by the invention. Compared with the prior art, the method provided by the invention has the advantages of high precision and low consumption, and fully meets demands on task scheduling policies of the cloud computing platform.

The invention discloses a network equipment health degree evaluation method based on dynamic and comprehensive weights. The method comprises the following steps: S1, determining a plurality of performance indicators for network equipment health degree evaluation, constructing a performance indicator system, and determining subjective weights of the performance indicators; S2, acquiring running data of network equipment to be evaluated, calculating values of the performance indicators, and establishing an evaluation matrix for the network equipment health degree evaluation; S3, calculating objective weights of the performance indicators; S4, calculating the dynamic and comprehensive weights of the performance indicators according to the corresponding subjective weights and the corresponding objective weights; and S5, according to the established evaluation matrix and the dynamic and comprehensive weights of the performance indicators, calculating a health degree of the network equipment to be evaluated, and carrying out the evaluation according to a health degree calculation result. The method provided by the invention has the advantages of high simplicity in implementation, high health degree evaluation precision and reliability and the like, and can achieve rapid and automatic evaluation.

A patent evaluating device comprises a data acquiring section (105) for acquiring items of patent data and patent attribute information on each item of patent data in a predetermined technical field from a patent database, a data classifying section (115) for classifying the acquired items of patent data into groups within a predetermined period of time, and an evaluation value calculating section (120) for calculating the evaluation value of each item of the patent data by using the patent attribute information on each of the patent data belonging to each group and by using the value determined for each group. With this, the value of a patent application or a patent right is adequately evaluated according to numerical information objectively determined and according to the progress information of the patent application or the patent right or the content information.

The invention provides an image quality evaluation method and device. The method comprises the steps: carrying out the target detection of a to-be-estimated image, so as to determine at least one target region; carrying out the quality evaluation of at least one target region, so as to determine the quality evaluation result of each of the target regions; and carrying out the quality evaluation of the to-be-estimated image based on the determined quality evaluation result of each of the target regions. The method provided by the invention enables an image quality evaluation process to focus on an AOI, and neglects the image quality of an inessential region, thereby achieving the quality evaluation of the to-be-estimated image. The method is high in evaluation speed, is higher in evaluation precision, and achieves the objective and effective evaluation of the quality of the to-be-estimated image.

The invention relates to a user-service awareness assessment method and device. The method includes: acquiring IP (internet protocol) messages of a control plane and a user plane on the mobile internet; integrating the IP messages with identical quintuple information into a service flow; integrating http streaming media service flows in the service flow to each http streaming media service operation record under single-user single-service granularity according to a redirector server IP address, user IP addresses, a GTP (GPRS tunneling protocol) tunnel ID (identifier) and time parameter; according to playing related parameters and download related parameters of the http streaming media service flows in the http streaming media operation records under the single-user single-service granularity, calculating a KQI (key quality indicator) which is enabled to indicate true service awareness of each single user. Therefore, assessment precision and assessment effect are improved.

An image quality objective evaluation method based on manifold feature similarity is disclosed, which firstly adopts visual salience and visual threshold to remove image blocks which are unimportant to visual perception, namely, uses roughing selection and fine selection; and then utilizes the best mapping matrix after block selection to extract manifold feature vectors of image blocks which are selected from original undistorted natural scene images and distorted images to be evaluated; and then measures the structural distortion of distorted images according to manifold feature similarity; and then considers effects of image brightness changes on human eyes and obtains the brightness distortion of distorted images based on an average value of image blocks, and finally obtains quality scores according to structural distortion and brightness distortion; which allows the method of the present invention to have a higher evaluation accuracy, and also expands the evaluation capacity to various distortions.

The invention relates to a track traffic power battery state of health (SOH) evaluation method. The method comprises the following steps: step one, based on a battery state of charge-open circuit voltage (SOC-OCV) model, extracting battery SOC-OCV model parameters a, b, c and d; step two, counting change trends of the SOC-OCV model parameters of more than five batteries along with aging, and obtaining development rules of battery SOC-OCV model key parameter values as the batteries age; step three, based on the development rules of the battery SOC-OCV model parameters as the batteries age, establishing function relations between SOHs and the model parameters in the first step by use of a linear regression method and obtaining a new SOH definition formula; and step four, evaluating the SOHs of the batteries based on the new SOH definition formula obtained in the third step. The rack traffic power battery SOH evaluation method provided by the invention can reflect the fundamental cause of battery aging and is quite high in precision.

The invention provides a Wiener process reliability analyzing method considering self-correlated measurement errors. The problem that an existing performance degradation analyzing method severely influences reliability evaluating precision is solved. The method includes the steps of randomly extracting a sample from a batch of products to be put in a test, collecting product performance degradation data, describing the real performance degradation process of the products according to the Wiener process, establishing a Wiener process performance degradation model considering the self-correlatedmeasurement errors, estimating unknown parameters of the performance degradation model through a likelihood function, and analyzing the product reliability according to the estimated unknown parameters. The method is a degradation reliability analyzing method of a linear Wiener process of the AR (1) measurement errors, the evaluating precision is effectively improved, universality is achieved, adaptability is higher, a reliability function analyzing expression under a given degradation failure threshold is given, and the basis is provided for subsequent reliability evaluation of the products.

The invention discloses a method for evaluating mustard sauce flavor grades by a taste system and an electronic nose, and belongs to the technical field of condiment analysis and identification methods. The method includes the steps of acquiring intelligent sensory data of mustard sauce by an electronic tongue taste system and an electronic nose olfactory system; performing digital processing for traditional sensory evaluation indexes; analyzing relations among the acquired sensory evaluation indexes, stoichiometric indexes and the intelligent sensory data by the aid of a random forest model; evaluating sensory grades of mustard sauce flavor. According to the method, objectivity and accuracy of sensory evaluation of the mustard sauce can be effectively improved, and the method is simple to operate, low in sample consumption and cost and short in consumed time and has high popularization and application values.

The invention relates to the technical field of environmental pollution evaluation, in particular to a risk assessment system of soil heavy metal pollution on human health, which can automatically assess the risk of the soil heavy metal pollution on the human health, save assessment time and improve assessment precision, and comprises a storage module, an input module and a heavy metal pollution risk evaluation module, wherein the storage module is used for storing parameters of physical and chemical properties and toxicological information of various soil heavy metal pollutants; the input module is used for inputting the types of the soil heavy metal pollutants of a region to be assessed, the ambient concentration and human health risk assessment parameters; and the heavy metal pollution risk evaluation module comprises a carcinogenic risk evaluation module, a non-carcinogenic risk evaluation module and a pollution risk level evaluation module, and is used for evaluating carcinogenic risk, non-carcinogenic risk and pollution risk level according to the types of the soil heavy metal pollutants, the ambient concentration and the human health risk assessment parameters.

The invention provides a stratum anisotropy information extracting and correcting method and system. The method comprises the following steps that an array lateral logging response chart and an anisotropy correcting chart are built through a plurality of different stratum models in a simulation way; four apparent resistivity curves of different radial detecting depths are obtained through underground measuring data measured by an underground array lateral logging instrument; the storehouse checking inversion is carried out by adopting the obtained apparent resistivity and the built logging response chart, and the stratum horizontal resistivity and the anisotropy coefficient are extracted; the stratum vertical resistivity is calculated according to the extracted stratum horizontal resistivity and the anisotropy coefficient; the apparent resistivity curves of different radial detecting depths are respectively corrected according to the extracted anisotropy coefficient and the built anisotropy correcting chart, and four corrected apparent resistivity curves are obtained. The method and the system adopting the scheme have the advantages that the complexity of the program design can be reduced, more precise stratum resistivity information is obtained, and the evaluation precision of oil and gas saturability is improved.

The present invention discloses a lithium ion battery state-of-charge dynamic assessment and long-acting prediction fusion method. The method comprises the steps of: employing the expanded Kalman filter method to perform assessment of the lithium ion battery state of charge to obtain a lithium ion battery state of charge SOCKEF; employing an echo state neural network to perform prediction of the lithium ion battery state of charge to obtain a lithium ion battery state of charge SOCESN; and finally performing weighing fusion of the lithium ion battery state of charge SOCKEF and the lithium ionbattery state of charge SOCESN to obtain a final lithium ion battery state of charge SOC. The lithium ion battery state-of-charge dynamic assessment and long-acting prediction fusion method improves the adaptation and the assessment precision of a current battery SOC detection method to overcome the restriction of SOC dynamic assessment of a single method, specifically selects a fusion method based on model and data drive and takes the consideration of SOC detection assessment dynamic timeliness and long-term long-acting prediction demands.

The invention relates to an electronic energy-saving lamp service life rapid detection method. The existing detection method is long in period and low in efficiency. The method of the invention includes that firstly two groups of electronic energy-saving lamps are placed under high temperature stress condition and subject to constant heat stress accelerated life test, so as to obtain the tested life value; and then the service life of test sample under normal temperature condition is calculated by combining arrhenius model according to the tested life value of the test sample under high temperature stress condition. The invention greatly shortens test and detection time, saves energy source and other experimentation cost and has higher life calculation evaluation accuracy.

The invention discloses an urban development land suitability evaluation method based on principal component analysis, and the method comprises the steps: selecting suitability evaluation index factors, carrying out the normalization of the evaluation index factors, and building a single-factor suitability evaluation model; carrying out principal component analysis on the single-factor suitabilityevaluation model, solving the weight of each principal component by utilizing an accumulated contribution rate, and establishing a comprehensive suitability evaluation model to obtain a comprehensivesuitability evaluation value; combining a Kriging interpolation method and a K_Means spatial clustering method to carry out spatial prediction and grading on the suitability evaluation of the urban development land; performing spatial diversity evaluation on the evaluation result by using a geographical detector, finally verifying the precision and effectiveness evaluation of the evaluation result, performing suitability statistics and evaluation, and developing a suitability extension direction analysis. According to the urban development land suitability evaluation method, the artificial subjective influence of evaluation index grading and index weight determination is avoided, so that the evaluation result has higher evaluation precision and effectiveness.

The invention relates to a computing method for double-fed wind power unit overspeed off-grid critical time. The computing method is characterized in that the method is started with setting up an electromechanical transient mathematic model after a DFIG is disturbed, the effects on the electromechanical transient of the factors such as the initial operation conditions, disturbance intensity and Crowbar protection motions of the DFIG are analyzed, the conditions reaching overspeed protection motions of a DFIG unit are deduced, and a wind power unit off-grid living example in a certain wind power field is analyzed through the provided method, and the wind power unit with the overspeed protection motions is correctly recognized according to the calculated time from acceleration to overspeed protection motion fixed values of rotors of all units. The computing method has the advantages of being simple and rapid in computing, high in evaluation accuracy and application value, wide in on-line application prospect and the like.

The invention discloses a method for rapidly evaluating an oil-water layer through array induction data, and belongs to the technical field of logging evaluation in oil exploration. The method comprises the steps of collecting single well array induction logging data, namely carrying out array induction logging, analyzing the array induction data, selecting a curve which reflects the undistributed stratum electrical resistivity and the flushed zone stratum electrical resistivity, evaluating stratum water characteristics on the whole well section through the provided method according to the selected curve, segmenting the processed well section according to the calculated stratum water characteristic values, determining the stratum water characteristic values of each section, evaluating the water saturation of a whole-well-section reservoir stratum through a formula according to the selected stratum water characteristic values of each well section, calculating and obtaining the water saturation value of each storage stratum single layer or each point, evaluating the oil-water layer with an evaluation standard according to the water saturation values of each layer of the storage stratum, and therefore achieving rapid recognition on the oil-water layer.

The invention discloses a comprehensive evaluation method of organic matter humification level. The comprehensive evaluation method mainly comprises a first step of collecting samples, extracting and preparing water-solubility organic matter and measuring organic carbon content (DOC) of the water-solubility organic matter, a second step of measuring a three-dimensional fluorescence spectrum and calculating a humification value of the organic matter, a third step of carrying out normalization processing on the humification value, a fourth step of establishing a projection pursuit model, a fifth step of carrying out a solution method for the model, a sixth step of comprehensively evaluating the humification level of the organic matter. The comprehensive evaluation method is easy and fast to calculate and accurate in evaluation result.

An embodiment of the invention provides a method and a device for correcting nuclear magnetic resonance logging porosity. The method includes: acquiring a well wall electric imaging logging image and nuclear magnetic resonance logging porosity corresponding to a target rock; establishing a nuclear magnetic resonance logging porosity correcting model according to size of the target rock, size of a gravel component, sizes of non-gravel components and porosity definitions; acquiring a proportion of the gravel component in the target rock according to the well wall electric imaging logging image; calculating a corrected nuclear magnetic resonance logging porosity according to the proportion of the gravel component in the target rock and the correcting model, wherein the corrected nuclear magnetic resonance logging porosity is a corrected value of the nuclear magnetic resonance logging porosity. Since the electric imaging logging image acquired according to an electric imaging logging technology is adopted for correcting the nuclear magnetic resonance logging porosity so as to obtain the corrected value of the nuclear magnetic resonance logging porosity, the situation that reservoir porosity determined by nuclear magnetic resonance logging is smaller than actual reservoir porosity of a stratum is avoided, and precision in evaluation of oil-gas reservoirs is improved.

The invention discloses a modeling method of accelerated degradation information fusion based on uncertain data envelopment analysis. The method comprises the following steps of: 1, collecting all available degradation data obtained by the product ADT and perform data preprocessing; 2, performing accelerated degradation modeling to obtain a confident reliability distribution of a single data source; 3, evaluating the ADT data source and determine the evaluation index; 4, performing uncertain DEA modeling to determine the relative efficiency of each ADT data source; 5, assessing and predictingthe life and reliability of the product. Through the above steps, the multi-source ADT data can be fused to conduct comprehensive reliability evaluation of products, which can reduce the cognitive uncertainty and improve the reliability and life evaluation accuracy of products. In the field of current ADT reliability evaluation, the lack of overall product information recognition caused by small samples and the inadequate use of multi-source ADT data sources are solved.

An embodiment of the invention provides an RPTSVM-based power system transient stability assessment method. By adopting an energy function index and a power system index to configure an original feature set, the number of dimensions of the feature set and redundant information can be reduced, and a new idea of sample set configuration is formed; a maximum correlation and minimum redundancy feature selection method is adopted to perform feature compression on the power system index and a projection energy function index, so as to find a power system feature sub set with high power grid transient change sensitivity, so that redundancy information can be further reduced, and number of dimensions of the feature can be reduced; after a regular term reconfigurable classifier is added to the optimization target function by the RPTSVM, power system transient stability assessment is performed, so that transient stability assessment stability can be ensured, the non-full-rank defects of a variance matrix in the transient stability assessment by the PTSVM can be avoided, and the generalization ability of the PTSVM assessment model is improved; and parameter optimization is performed by a genetic algorithm, and the population quantity is reasonably selected, so that the calculation time can be shortened under the premise of ensuring that the optimal parameter combination can be selected.

A construction damage assessment method based on a single post-earthquake POLSAR image comprises the following steps: noise removal, survey region extraction and partitioning are performed on an original POLSAR image; non-construction areas are detected; constructions with an NCCC greater than a set threshold are classified as a collapsed construction class, constructions with an NCCC smaller than or equal to the set threshold are classified as a non-collapsed construction class, and pre-assessment is performed; when a homogeneity textural feature HOM of a block which belongs to certain serious damage class is greater than or equal to a preset HOM texture threshold, the block is changed to belong to a medium damage class; a final damage degree classification result is subjected to precision evaluation. According to the construction damage assessment method, detection and evaluation of collapsed constructions are performed through only single post-earthquake perfect-polarization SAR data, evaluation precision is improved, and dependence on pre-earthquake data of disaster monitoring in the prior art is reduced.

The invention relates to the technical field of environmental investigation, and discloses an environmental investigation method for groundwater chlorohydrocarbon pollution, which comprises the following steps: S1, first-stage investigation is made; S2, result analysis is made: if a first-stage survey confirms that there is no possible pollution source in a working area and a surrounding area currently and historical, the survey activity can be ended, and if the pollution source existing inside and outside the working area cannot be eliminated, the second-stage environmental survey is carriedout; S3, second-stage investigation and preliminary sampling analysis. According to the invention, geological and hydrogeological conditions of an investigation area are found in detail; pollution source distribution of an investigation area is found out in detail, types and components of concerned pollutants are determined, the spatial distribution range of main pollutants in soil and underground water is delineated, the pollution degree of the soil and the underground water of the investigation area is evaluated and subjected to risk assessment, and a scientific basis and data support are provided for next-step treatment, restoration and safe utilization work. Development of groundwater pollution dynamic monitoring.

The invention discloses a tire and pavement contact pressure characteristic-based pavement skid resistance condition evaluation method. The tire and pavement contact pressure characteristic-based pavement skid resistance condition evaluation method comprises the following steps: 1. adopting at least two pressure induction films, placing the pressure induction films on a bottom surface of a tested automobile tire and between the tire and different pavements to be tested; 2. contacting the tire of the tested automobile to the pressure induction film in a dead weight manner; 3. taking out the pressure induction film; (4) scanning the pressure induction film to acquire the pressure intensity value of each tested point of each pressure induction film; (5) determining the area M having the pressure intensity value of 0-0.2MPa of the contact surface of each pressure induction film and the tire; (6) calculating P which is equal to M / the area of the contact surface of the pressure induction film and the tire respectively; and (7) comparing all P values and evaluating the pavement skid resistance of all pavements to be tested. According to the method, the pressure induction film is utilized for measuring the pressure distribution of the tire and the pavement, the pavement skid resistance condition can be evaluated and the evaluation result is accurate; and besides, according to the tire and pavement contact pressure characteristic-based pavement skid resistance condition evaluation method, the cost is low, the use is convenient and the popularization is easy.

The invention discloses a network safety management system based on an alarm strategy The system comprises a safety event collecting module, a real-time risk evaluation module, an alarm strategy obtaining module and an alarm execution module; the safe event collecting module normalizes safety logs via a network safety device, generates a safety event and collects the safety event; the real-time risk evaluation module evaluates the risk degree of a safety event; alarm information is emitted for the safety event whose risk degree is greater than a risk degree threshold; the alarm strategy obtaining module receives the alarm information and obtains the corresponding alarm strategy; and the alarm execution module executes the alarm according to the alarm strategy. According to the invention, the alarm information itself is corrected and managed, the controllability, instantaneity and flexibility of network safety are improved, and the reliability of output alarm information is ensured.

The invention relates to an instrument flight program three-dimensional design system which is composed of a system basic data management module, an automatic flight program protection area two-dimensional generation module, an automatic obstacle evaluation module, an automatic flight program protection area three-dimensional presenting module and a database module. The automatic obstacle evaluation module can be used for calling data in the system basic data management module, achieving automatic obstacle evaluating on a generated flight program protection area, a navigation facility shielding surface and the like and sending an evaluation result to the automatic flight program protection area two-dimensional generation module to check whether the flight program protection area can keep the specified safety margin on obstacles. The automatic flight program protection area three-dimensional presenting module is used for conducting three-dimensional dynamic presenting on the flight program two-dimensional flight program protection area and the like. The instrument flight program three-dimensional design system can be used for achieving the functions of automatically generating the flight program protection area, automatically evaluating the obstacles and conducting three-dimensional presenting and perpendicular exaggerating on the flight program protection area and a high-precision mass DEM database and the like.

The invention discloses a signal assessment and improvement system of a remote monitoring device and a control method. The system comprises an elevator control system used for controlling elevator running, the remote monitoring device used for receiving and transmitting elevator running information, a signal base station for transferring data and a cloud server; and the remote monitoring device comprises a data processing module and an antenna module, and the antenna module comprises an antenna and a signal strength detection device. During installation or debugging of the remote monitoring device, the remote monitoring device continuously transmits testing data packages to the cloud server through the signal base station, the cloud server responds the remote monitoring device and feeds back testing data, the remote monitoring device receives the fed-back data and conducts statistics on signal reliability at the position, and the best antenna placing position at the current environment is comprehensively operated in cooperation with signal strength data fed back by the signal strength detection device. Meanwhile, when an elevator runs, telecommunication abnormal failures are fed back when it is detected that the current signal reliability is too poor.

The invention relates to a fuzzy variable-weight engineering geological environment quality evaluation method comprising the following steps: establishing an engineering geological environment quality evaluation hierarchical structure model; acquiring engineering geological data corresponding to all participating indexes in an area to be evaluated; dividing the area to be evaluated into m basic evaluation units; establishing the evaluation index matrix and the variable weight matrix of each basic evaluation unit; calculating the variable-weight comprehensive evaluation value of each basic evaluation unit according to the evaluation index matrix and the variable weight matrix corresponding to the basic evaluation unit; getting the engineering geological environment quality grade of each basic evaluation unit according to the variable-weight comprehensive evaluation value of the basic evaluation unit; and clustering the basic evaluation units of the same engineering geological environment quality grade through use of a clustering method to get an engineering geological environment quality comprehensive evaluation partition map. The method has the advantages of high evaluation precision, objective and reliable evaluation result, and the like.

The invention discloses an importance sampling Monte Carlo power system reliability evaluation method based on a geometric optimization-minimum variance method. First, a geometric optimization method in the field of planning and a variance minimization model in importance sampling are combined together, and a variance minimization model in reliability evaluation is solved through geometrical optimization, and then, reliability evaluation is conducted using obtained importance sampling parameters. Compared with the traditional reliability evaluation method based on importance sampling, the reliability evaluation method of the invention has the characteristics of smaller convergence variance, faster convergence and higher evaluation precision. By improving the evaluation speed and evaluation precision of system reliability evaluation and especially by capturing small-probability / highly-influential rare events, the reliability nuance between different power grid planning schemes can be evaluated quickly, and a quantitative and accurate auxiliary reference basis can be provided for the selection of power grid planning schemes.

The embodiment of the invention discloses a method and device for evaluating a target detection algorithm based on an unmanned vehicle. The unmanned vehicle is provided with a camera, a vehicle body signal sensor, a laser radar and a millimeter-wave radar. The method comprises the steps that: continuous images collected by the camera, vehicle body signals collected by the vehicle body signal sensor, radar data corresponding to the laser radar and millimeter-wave radar data corresponding to the millimeter-wave radar in the driving process of the unmanned vehicle are acquired; the continuous images and the vehicle body signals are input into the target detection algorithm, so that a prediction position and a prediction speed of each prediction target are obtained; a true value position and atrue value speed of each true value target around the unmanned vehicle at each sampling moment are calculated according to the radar data and the millimeter wave radar data; and an evaluation resultof the target detection algorithm is calculated according to the prediction position and the prediction speed of each prediction target and the truth value position and the truth value speed of each truth value target. According to the method and device of the embodiment of the invention, the evaluation precision of the target detection algorithm can be improved.