123results about How to "Reasonable assessment" patented technology

The invention relates to an evaluating system and method for community influence in a social network. The method comprises the steps that a social network chart with social network users as nodes and user relationships as sides is built; according to the social network chart, the community structure of the social network is obtained by carrying out community division through the label propagation algorithm; according to the social network chart and matrixes which communities belong to, the parameter of the community influence is calculated, and the initial influence of each community is generated; according to the transmission probability model of the influence, an influence transmission probability matrix is generated; according to the influence transmission probability matrix and the community influence iterative computation model, the community influence is iterated and upgraded until the iteration end condition is met, the influence value of each community is obtained, and the sequence of the community influence, namely, the influence estimation result of each community in the social network is obtained after normalization. The system and method can effectively analyze the distribution of the community influence in the social network and can be used for high-influence community mining, thereby being capable of being applied to the fields of network marketing and the like.

The invention relates to the field of expansion planning and safety analysis on electrical power systems. In order to provide a systematized method and a relatively perfect assessment process for the safety assessment on a planning scheme, the technical scheme adopted by the invention is as follows: a method for assessing a safety value of a planning scheme for an electrical power system containing large-scale wind power comprises the following steps: 1, establishing a power supply-power grid unified planning model for taking account of static and dynamic safety values of the system; 2, beginning to carry out detailed operation simulation on candidate planning schemes; 3, after units are combined, carrying out safety assessment on the system time interval by time interval; 4, carrying out comprehensive safety control optimization on an contingency set by using a 'positive constraint and relaxation method' so as to obtain the optimal division of a preventive control contingency set and an emergency control contingency set; and 5, obtaining the total cost of the planning scheme, and taking the total cost as a basis for evaluating the planning scheme. The method disclosed by the invention is mainly applied to the expansion planning and safety analysis on the electrical power systems.

The invention relates to a method for measuring the optical gyroscope on line by the integrating optical modulator, and the measuring system comprises optical fiber interference circuits, a high-precision stable light source, a light-sensitive detector, a head amplifier, the controlling section of modem, the high precision square wave, a step wave generator and the adjustment. The method comprises the following steps: a) injecting the light source to the Y waveguide modulator after coupling, measuring the depletion, light splitting proportion of the device according to the input and output parameter; b) coupling the Y waveguide modulator with the interometer, applying the manual step wave and square wave signals to the device to be measured; c) outputting the electric signal after interference by the signal mediating system, measuring the dynamic response feature quantificationally through the slope of the reset curve which is formed after the device responses to the step wave.

The invention discloses a tailing pond layered index safety assessment and early-warning method and system. The method comprises the steps that a three-level safety index system is built, wherein the three-level safety index system comprises four second-level indexes which are the stockpiling system, a drainage system, a risk system and a management system and fifteen three-level indexes which are the pond water level, the rainfall capacity and the like; a tailing pond safety assessment model is built, and the safety index system is utilized for assessing the overall safety state of a tailing pond; a tailing pond safety early-warning model is built, and early-warning judgment is carried out; the safety early-warning model comprehensively figures out a dynamic change curve of the future pond water level in the flood season by means of data collected in real time and weather forecast information transmitted by the network, the data collected in real time and measured by the safety assessment model to carry out comprehensive safety assessment and evaluation on the tailing pond, dangerous trend classification is carried out according to assessment, then the classification information is put into a pond water level-dam break model, the dam break risk is comprehensively calculated according to the classification information and a predicted pond water level value, and early-warning judgment is carried out according to the risk. The early-warning effect is accurate, reasonable and comprehensive.

The invention discloses a county-level crop planting area remote sensing statistic sampling survey scheme design method. Multi-period up-to-date GF-1 16-meter-width images are adopted as a data source; a decision tree classification method is constructed to perform automatic interpretation, so that the spatial distribution condition of crops in a research area can be obtained; with the spatial distribution data of the crops adopted as a sampling population, on the basis of the arable land area and crop planting scale of the research area, a PPS sampling method is adopted to select a general survey region; various sample unit sizes and various sample unit quantities are designed in the selected general survey region, the quadrat unit sizes, quadrat sample unit quantities, sampling methods and calculation methods are combined randomly, the calculation results of the statistic sampling survey schemes of different combinations are compared with the planting area of target crops which is obtained through the data interpretation of GF-2 0.8-meter-resolution images; and analysis is performed according to the overall sampling accuracy, sampling stability and minimum sample capacity of result data, and a remote sensing statistic sampling survey scheme most suitable for the target crops of the research area can be obtained.

The invention provides an alarm generation method and system. The alarm generation method is carried out in a cloud computing environment on the basis of a big data analysis technology. The method includes the following steps that: the operation data of a monitoring object and the operation data of at least one association object are collected on the basis of a predetermined collection policy, wherein the association objects are objects directly or indirectly affecting the operation state of the monitoring object; the pre-stored historical operation data of the monitoring object and the at least one association object are acquired on the basis of a predetermined data analysis policy, and data analysis is performed on the collected operation data of the monitoring object, the operation dataof the at least one association object and the acquired historical operation data of the monitoring object and the at least one association object, so that the performance trend and state change of the monitored object is obtained; and intelligent alarm analysis decision is performed on the performance trend and state change of the monitored object on the basis of an alarm policy, whether an alarm is to be generated is determined.

The invention relates to an intelligent blind-guide method comprising the steps of obtaining position information; planning and analyzing a route; performing real-time analysis on road conditions; judging whether traffic signal detection for an intersection is needed according to a map and positioning information; analyzing the state of traffic information signal lights and prompting a user; establishing a Gaussian mixture model and performing background analysis on obtained road condition images to obtain an image background and further obtain foreground image information; performing feature analysis on the foreground image information to judge the road information and passenger and vehicle information and prompting the user. The method can perform accurate and comprehensive detection and reasonable evaluation on complex road conditions, can provide reasonable and timely prompts for users, can provide convenience for going out of special crowds, in particular the blind and the old, fulfills the functions of accurate positioning, route navigation, road condition detection and voice prompt, and is worthy of extensive promotion.

The invention discloses a multi-factor based photovoltaic power station middle-and-long-term generating capacity prediction method including the following steps of A) based on the data of an environment detector and a weather station, acquiring the power station dimensions, inclination angles, and historical daily level radiation quantities, and selecting the number of days in the month, the date sequence number in a year, solar constants, and the ground reflectivity; B) calculating the annual inclined plane total radiation quantity I; C) calculating the comprehensive efficiency of a photovoltaic power plant; D) calculating the annual effective hour number of the photovoltaic power plant; E) calculating the generating capacity of the first year; and F) calculating the generating capacity value of the nth year and the total generating capacity for many years of the photovoltaic power plant. The prediction method is simple in calculation, efficient, and stable, and has good prediction benefits and good application prospects.

The invention relates to a method for evaluating the interferences of different systems to a terminal, which comprises the steps of evaluating spurious interference, intermodulation interference and adjacent channel interference generated by each RRU base-station transmitter; evaluating the interferences of the different systems to the terminal of each RRU base station transmitter according to the spurious interference, the intermodulation interference and the adjacent channel interference; and evaluating the interferences of the different systems to the terminal of all the RRU base station transmitters according to the interferences of the different systems to the terminal of each RRU base station transmitter. Meanwhile, the invention further provides the method for evaluating the comprehensive interferences to the terminal, which comprises the interferences of the system and the interferences of the different systems. The use of the method can better evaluate the interferences of the base station transmitters of a multi-mold system to the terminal.

The invention discloses a power system transient stability assessment method based on big data, and the method comprises two stages: sample training and result evaluation. The sample training stage comprises the steps: carrying out the centralized training and learning of ELMs through employing big data of a power system, and also completing the confirmation of each transient stability characteristic quantity weight parameter. The result evaluation stage comprises the steps: firstly building a transient stability key characteristic library; secondly extracting key characteristics in current real-time data, and transmitting the key characteristics to a trained EMLs; finally carrying out the comprehensive analysis of the output result of the EMLs through a decision evaluation module, and giving a transient stability assessment result and the confidence of the current result. The method takes big data as the background, is based on the reasonable dimension reduction and complete use of mass data of a power grid, is based on a learning machine cluster, and meets the requirements of complete and real-time safety early warning of an intelligent power grid.

The invention belongs to the field of reliabilities of numerical control machine tools, and particularly relates to a precision reliability analysis method for a heavy numerical control machine tool based on a multi-body system kinemics theory. The precision reliability analysis method comprises the following steps: constructing a relation model between the output precision error of the heavy numerical control machine tool and a factor affecting the precision of the machine tool, fitting a change relation of the factor affecting the precision of the machine tool along with the time by a random process, finally combining on-site data or data of the same type of sample, and introducing a Bayes evaluation method to update the precision error model of the heavy numerical control machine tool, thus realizing evaluation of the precision reliability of the machine tool. The precision reliability analysis method has the beneficial effects that the Bayes evaluation method is introduced to fit and correct the change tendency of respective factors causing a motion precision error of the machine tool, so that the difficulty that a sufficient statistical sample cannot be formed due to a 'small sample' is solved; and therefore, more scientific and reasonable evaluation is performed on the dynamic reliability of the precision error of the heavy numerical control machine tool.

The invention provides a multitask multirole remote operated vehicle (ROV) cooperative training simulating system. A server stores, arranges, and invokes all kinds of data packets to comprehensively present various all kinds of data in a dynamic simulation manner, provide real-time simulation scenarios and present on-site demonstration of ROV states for training personnel, continuously receive instructions inputted by the training personnel, process the instructions, store the processed instructions as new simulation data, and compare the new simulation data with historical simulation data toprovide optimal operation indications in real time for the training personnel; a monitoring management end monitors an operation process of a whole training system, and performs optimization and management for the server; and a control panel terminal trains the personnel to receive three-dimensional simulation scenarios by a combined display and real-time state information of an operated and controlled ROV, and perform actual manipulation to an ROV and configuration tools thereof in a virtual scenario through a rocker device, a speed adjusting device and an operation handle device. The multitask multirole ROV cooperative training simulating system can accurately evaluate a training result, record a training process, and reasonably evaluate all completion key points and cooperation key points.

The invention provides a swimming stroke recognition method based on a smart band and a sports plan based on the smart band. Four normal swimming strokes of freestyle swimming, breaststroke, backstroke and butterfly stroke can be recognized. On the basis of a bayesian classification algorithm, according to different types of swimming stroke and physical quantities detected by the smart band, a swimming stroke recognition method is established, and moreover, with the combination of the sports time detected by the smart band and physical quantities such as the pulse beat, a sports plane including functional capacity evaluation is provided. By adopting the swimming stroke recognition method, high-standard requirements of people on healthy sports can be met.

The invention relates to a method for evaluating the output characteristic of a wind power plant, and the method comprises the steps: selecting a reference unit in the wind power plant, and measuring the wind power data of a cabinet front of the reference unit through a laser radar; collecting the operation data of the reference unit, and carrying out the time synchronization of the above two pieces of data; calibrating the landform of a place where a reference unit is located through a computational fluid mechanics calculation method, and correcting the wind power data according to a calibration result; obtaining a wind speed distribution probability density function following a three-parameter Weibull distribution through the corrected wind power data; calibrating an anemorumbometer of a tested unit; building an extrapolation function of other units and the tested unit; building a cabin front wind resource distribution database of each unit arrangement place of the wind power plant; importing the database into a wind power evaluation system database; and evaluating the output characteristics of each unit or the whole wind power plant. According to the embodiment of the invention, the operation conditions of the unit can be mastered and evaluated in real time, and the method can provide reliable wind power plant information for power scheduling, and is high in practicality.

The invention discloses a modern transmission network false data attack defense method based on a protection measurement point in the field of information security research of a power system. The method provided by the invention comprises the steps that a false data attack vector optimization model is constructed based on a traditional power system state estimation theory; according to the optimization model, a false data attack defense measure based on indexes Vk and Rk is provided; the basic idea is to reduce the number of vulnerable nodes vulnerable to attacks in the power system and to enhance the overall ability to deal with false data attacks; and according to an importance index Ik, the defense measure is realized, namely the target of the optimization indexes Vk and Rk is realized by protecting a high measurement point of the importance index Ik. According to the invention, the important measurement point is protected to effectively improve the attack cost and the attack difficulty of an attacker.

The invention provides a bank performance appraisal system. The system comprises a bank database server and a terminal device connected with the bank database server through an interface. The terminal device comprises an employee management module, an appraisal indicator setting module, an appraisal standard setting module, a weight setting module, a data acquisition module, a performance statistical module and a performance-related pay calculation module, wherein the appraisal indicator setting module is used for setting all appraisal indicators according to posts of employees; the appraisal standard setting module is used for setting appraisal standards according to all the appraisal indicators; the weight setting module is used for setting weights of all the appraisal indicators; and the data acquisition module is used for acquiring indicator data completed by all the employees from the bank database server according to the set appraisal indicators. Through the bank performance appraisal system, the appraisal indicators, the appraisal standards and the weights of all the indicators can be self-defined, the requirements of different banks for different appraisal indicators of the employees are met, performance appraisal is reasonable, and meanwhile the working abilities of the employees can be well fed back, so that the employees are helped to improve working efficiency and the working abilities.

The invention discloses a system for distinguishing the stress of a driver based on electrocardiosignals and geographic information, which is characterized by comprising a photoelectric pulse sensor and a circuit part, and a micro controller is connected with a vehicle sensor and a GPRS or Beidou navigation system; whether the current driving state is secure is evaluated according to electrocardiogram information, vehicle operating state and traffic environment information acquired by the micro controller, and when the current driving state is insecure, an alarm is made; and the distinguishing method comprises the following steps: a) determining signal input; b) acquiring electrocardiosignals; c) calculating a RR interval; d) calculating the powers of high and low frequency bands; e) determining whether mutation occurs in the RR interval; f) determining whether the powers of high and low frequency bands exceed a threshold; g) acquiring traffic environment information; and h) making a voice alarm. According to the system and method disclosed by the invention, by using the combination of acquired electrocardiosignals and physiological indexes, the stress of the driver is distinguished, so that the driving safety status can be scientifically evaluated and forecasted, therefore, the system and method disclosed by the invention have remarkable beneficial effects, and are convenient for popularization and application.

The present invention provides an area electric energy quality integration assessment system. The assessment system comprises an electric energy assessment system module, a weight calculation module, a single monitoring point electric energy quality assessment module based on cloud inference and an area electric energy quality assessment module. The present invention further provides the assessment method of the area electric energy quality integration assessment system. The area electric energy quality integration assessment method and system construct a cloud inference assessment model through building the electric energy quality assessment system and performing cloud processing of the electric energy quality assessment index grade threshold value to realize the indetermination division of the electric energy quality classification grade boundary, and employ the subjective and objective integration weighting method to effectively solve the problems that the subjective factor influence is big, the calculation is complex and the assessment object is observation point non-area in the electric energy quality integration assessment. The assessment method provided by the invention can complete the mapping conversion of the electric energy quality integration assessment from quantification input to qualitative inference and then to the quantification output, and therefore, the assessment process is more reasonable, and the assessment result is more credible.

The invention discloses an enteroscopy quality evaluation method and device based on image recognition and a storage medium. The evaluation method comprises the following steps: splitting a video acquired in an enteroscopy process into a plurality of examination images; dividing the plurality of inspection images into close-shot mode images and non-close-shot mode images based on the first classification condition and the second classification condition; and accumulating the collection duration of the close-shot mode image, and evaluating the enteroscopy quality based on the collection duration of the close-shot mode image. According to the method, the collection time of the close-shot mode image is used as an evaluation index, a scientific and reasonable enteroscopy quality evaluation standard is established, and an endoscopy doctor can be guided to improve the collection time of the close-shot mode image by changing an examination operation mode within a shorter enteroscopy time; furthermore, a longer close-range view field capable of effectively observing intestinal mucosa is obtained, so that the examination quality of the enteroscope is improved.

A device for measuring the optical ring of gyroscope on-line modularity, including circuit conciliating modular, light leading-in modular, optical ring modular, the light leading-in modular provides the power and steady polarizing coherent light for the optical ring, transmits the optical interference signal to the electrical signal and exports to the circuit conciliating modular which connected with the light leading-in modular through the electric cable, which can measure, control and output the signal of the whole optical path, the measured optical ring modular is connected with the output end of the light leading-in modular through two pigtail optical fiber being protected, The measurement of the optical ring is in the actual condition of the optical gyroscope and the output and input are identical with the actual use, it not only tests the parameter of the optical ring such as depletion and reciprocity but also tests the system response in the temperature, impact and vibration.

The invention discloses a cloud platform security situation awareness method. The cloud platform security situation awareness method comprises the steps of 1) selecting a plurality of basic evaluation points and determining a quantized value of each basic evaluation point; and selecting a plurality of floating evaluation points and determining an initial value of each floating evaluation point; 2) updating the quantized value of each floating evaluation point periodically based on collected cloud platform information, wherein the quantized value of each floating evaluation point in the current period is updated based on the evaluation value of each floating evaluation points in the previous period and a security floating factor in the current period; 3) dividing the cloud platform into a plurality of security layers, fusing the quantized values of the evaluation points belonging to the same security layer to obtain an evaluation value C of the security layer, wherein the evaluation points include the basic evaluation points and the floating evaluation points; and 4) calculating a security evaluation result Q of the cloud platform based on the evaluation value of each security layer of the cloud platform and determining the security situation of the cloud platform. According to the cloud platform security situation awareness method, the security situation of the whole cloud platform can be monitored and evaluated, the operation is simple and convenient, and high security and reliability are achieved.

The invention belongs to the technical field of transmission line icing risk assessment, in particular to a transmission line icing risk assessment method. The method comprises the following steps: according to the possible influence degree, influence range and development trend of transmission line icing event, the transmission line icing state risk grade is divided into five grades according tothe ice thickness range; the final risk assessment indexes are extracted from meteorological factors, environmental factors and route parameters, and the route icing risk assessment index system is established. Consistency and dimensionless pretreatment of indicators; determining the Weighted Standardized Decision Matrix by Entropy Weight Method; the TOPSIS method is used to determine the positiveand negative ideal solutions of weighted standardized decision matrices. The matter-element extension method is used to divide the positive and negative ideal solution intervals and calculate the closeness degree. Calculating the eigenvalue, dividing the grade of each evaluation scheme, and judging the grade of the evaluation object. The invention is used for evaluating the icing risk of transmission lines and provides support for the risk management work of the power grid management department.

The invention discloses an adaptive rate parameter setting method of a model reference adaptive permanent-magnet synchronous motor speed sensorless control algorithm. According to the method, an open-loop transfer function of a system is obtained by linearization on a reference adaptive model and a stability condition thereof, a cutoff frequency and a phase of an open-loop system are calculated bycombining a gourdain method, a stable condition of the open-loop system is given out by combining an automatic control theory, and the adaptive parameter adjustment method is given out when the cutoff frequency and phase margin do not conform to a relevant condition. With the adoption of the method, and adaptive parameter setting of the model reference adaptive permanent-magnet synchronous motorspeed sensorless control algorithm can be achieved very well.

The present invention provides a credit evaluation method and a system, a storage medium and a terminal device. The method includes the following steps: classifying the text information obtained in credit verification to obtain the text information of each classification; performing text word division on the text information of each classification to obtain the characteristic words for this classification; based on the characteristic words of the various classifications, establishing a credit evaluation model; and according to the text information of a to-be-evaluated client and the credit evaluation model, obtaining a credit evaluation result for the to-be-evaluated client. The credit evaluation method and the system, the storage medium and the terminal device of the present invention have a wide range of applications and meet the credit evaluation needs of clients with various characteristics. The evaluation result is accurate.

The invention discloses a credit control prompting method and device and relates to the technical field of credit control. The method includes the following steps: the account information of users isobtained, whether the users are credit monitoring objects or not is judged, the contrast threshold is obtained according to the overdue sum monitoring range, contrast is performed according to the preset threshold and the arrearage quota to judge whether the user are in arrearage or not, grade assessment and credit prompting are performed on the users, and the credit grade is generated according to the contrast result of the arrearage quota and the preset threshold. Through accessing an information input interface module and an information output interface module to the credit control prompting device, the credit grade assessment model database of different users is established and the preset threshold model database matching the account information of the users, different monitoring plansare adopted for different users, the user payment reminder message and the credit prompting information are transmitted to the clients through various forms and devices of the Ethernet, and the credit control prompting speed and the diversity of the mode and platform of the arrearage and credit information pushing are improved.

The invention discloses a key node and influence domain analysis method for a power communication network, and the method comprises the steps: building a communication channel reliability model of communication interruption according to components of communication equipment in the power communication network and a safety and stability control device; analyzing the probability of communication service caused by high delay of the communication channel, and establishing a communication channel reliability model based on communication channel delay probability distribution; establishing a system protection communication channel reliability model comprehensively considering communication interruption and communication delay, acquiring the subjective weight of each index of the communication service through an analytic hierarchy process, and obtaining the objective weight of each index through an entropy weight method; obtaining a comprehensive weight according to the subjective weight and the objective weight, and determining the importance of each node and the communication link according to the importance of each index and the corresponding comprehensive weight; and obtaining the influence domains of the communication link and the communication node through an influence domain analysis method of the communication node and the communication link. According to the invention, the reliability of the communication channel of the power communication network can be evaluated more accurately.

The invention provides an extreme evaluation method and system for flood events induced by heavy rainfall. According to the method, multi-source information such as extreme rainfall and flood loss iseffectively fused, quantitative analysis and accurate calculation of the rareness, occurrence intensity and breaking strength of flood disasters induced by heavy rainfall are achieved, and compared with a traditional single evaluation method only depending on rainfall, a recurrence period or a disaster index, the result is more reasonable and reliable. Practical application results show that the method has good identification capability, can comprehensively and accurately evaluate the extreme property of flood disasters induced by heavy rainfall, and provides a new approach for detection and evaluation of extreme rainfall flood disasters under climate change conditions.

The invention belongs to the technical field of UUV autonomous control, and particularly relates to a UUV dynamic threat situation assessment method. The method can effectively solve the underwater dynamic threat situation assessment problem of the UUV, accurately assesses the threat situation at the current moment and within a period of continuous time, and can obtain the threat degree sequence of various current threats through sensitivity analysis. According to the method, a static Bayesian network or a dynamic Bayesian network is not singly used for evaluation, but the static Bayesian network and the dynamic Bayesian network are combined for use, and an environment, platform and task three-level evaluation network is used, so that an evaluator can conveniently know the conditions of all parts of the current UUV system, and meanwhile, a threat mode of each threat can be reasoned out; and finally, starting from the whole, a static network is used for carrying out sensitivity analysison the whole network, an online quantitative qualitative evaluation result is given for threats of an environment type, a platform health type and a task type sensed on site, input information is provided for subsequent autonomous control of the UUV, and the most urgent threat problem to be solved at present is decided.

The invention discloses a subjective and objective weight integration-based multi-feed DC drop point scheme evaluation method, and belongs to the technical field of electric power system operation and control. The method comprises the following steps of: carrying out comparison on the significance of all of the multi-fed DC drop point scheme evaluation indexes in pairs, and establishing an evaluation matrix; solving subjective weights of the evaluation indexes through a subjective weight model; calculating each index of an AC system under each multi-feed DC drop point scheme through electric power system simulation software BPA and solving objective weights of the evaluation indexes through an objective weight model; on the basis of the solved subjective weights and objective weights, solving a comprehensive weight of the indexes through a comprehensive weight model; and obtaining the multi-feed DC drop point scheme evaluation indexes on the basis of the comprehensive weigh. The method disclosed by the invention can be widely applied to the evaluation of DC drop point schemes of AC large power grids, and is particularly suitable for the evaluation of DC drop point schemes of AC large power grids which are 500 kV or above.