47 results about "Critical index" patented technology

The present invention provides a method an apparatus for adaptively refining the sampling within an IP network performance monitoring and diagnosis framework. This ability to adaptively adjust the resolution of the sampling can enable variable accuracy and detail in the related IP network analysis. The sampling resolution can be defined as, for example, the load on the network in terms of the rate of packet transmission, the statistical variance thereof and the complexity of the sampling procedure. Each sampling and analysis procedure determines one or more network parameters referred to as critical indicators. Decisions for subsequent samplings and actions are made based on the determination of these critical indicators. As such various evaluation activity levels are defined by conditions that can be checked for and detected within the context of that activity level. A feedback / feedforward process can be used to enhance the resolution of subsequent samplings, for example movement to a more detailed activity level, if the need is required. In addition, the present invention can support activities such as automated remediation wherein problems in a given IP network path that are identified during the sampling and diagnostic evaluation thereof are subsequently resolved by making changes in the path. The present invention can automate and enhance the monitoring, diagnosis and remediation processes, thereby reducing human involvement until human intervention may be required. In addition, the automatic functionality inherent within the present invention can enable the sampling to be scalable and responsive to changes in IP network conditions as they arise.

The invention discloses a public-transit-network layout optimization method. The method comprises the following steps that key indexes determining backgrounds ksi<1> of travelers are obtained; parameter indexes determining the public transit operation service level eta<2> are obtained; key control indexes determining the tolerance eta<1> of the travelers are set; key indexes S<x> influencing the travelers to judge the public transit service satisfaction degree are determined; control indexes E<BX> influencing public transit operation benefits are determined; the traffic capacity C of a public transit network of a city is worked out; an optimal object model of the layout of the public transit network is established; a layout scheme of the public transit network of the city is determined; whether the layout scheme of the public transit network meets the requirements of the optimal object model or not is judged, wherein if yes, the layout scheme of the public transit network is output, and if not, measurement and calculation in the last step are conducted, and the layout scheme of the public transit network is further optimized. By means of the public-transit-network layout optimization method, contradictions between public transit service differences pursued by different types of travelers and the public transit operation benefits can be balanced, the public transit service satisfaction degree can be increased, and the degree of loyalty of the travelers to the public transit service can be increased.

The invention relates to a data processing method and device for a customer service staff scoring system. The method includes the following steps that: a plurality of key indexes are automatically identified and analyzed from a large number of preset evaluation indexes based on a sparse regularization model; the weights of the plurality of key indexes relative to customer service scoring can be determined through adopting an analytic hierarchy process; and the comprehensive score of customer service staff is calculated according to the weights of the plurality of key indexes and the actual index values of the key indexes. Compared with the prior art, and according the method of the invention, the coefficient regularization method and the analytic hierarchy process are combined together, and therefore, scoring on the customer service staff can be realized automatically, and the workload of scoring personnel can be decreased, and work efficiency can be improved.

The invention discloses a virtual organization-based key performance indicator (KPI) analysis method, and belongs to a data analysis method. The method comprises the following steps of: defining the KPI for determining the key indicator of evaluating subordinate enterprises and a computing mode; defining enterprise analysis dimensions for defining the analysis angle of the subordinate enterprises; defining a virtual organization and appointing a corresponding relationship between the virtual organization and a standard organization and the dimension attributes of the virtual organization; automatically forming an analysis organization tree for the subordinate enterprises according to various dimensions, uniformly processing the KPI and storing in a KPI warehouse; and analyzing and displaying data in the KPI warehouse in various forms. Compared with the prior art, the method can improve the dimension flexibility of a KPI statistical analysis unit, improves the automation degree of forming the KPI for the subordinate enterprises according to the dimensions and reduces the work complexity of KPI analysis personnel.

The invention provides an SOA service real-time monitoring and reporting and performance measurement system comprising an aggregation calculation module used for realizing aggregation calculation of critical service interior data indexes, and a service performance measurement module connected with the aggregation calculation module and used for measuring the service performance of a monitored device, the SOA service real-time monitoring and reporting and performance measurement system can specially report, collect and monitor critical indexes during the operation of interfaces, service interior and business data, mutually decouple the critical indexes with the running services, can collect contents of monitoring files of machine devices to a data processing program in real time, can calculate the service performance of a service member of the monitored device in real time, and satisfies the increasing micro service management demands of companies.

The invention particularly relates to a PTN network optimization simulation method and a system. The method comprises steps that step 1, key indexes for quantitatively evaluating a PTN network are determined; step 2, a simulation model of the PTN network is constructed according to performance parameters of PTN network elements, optical cable distances among the network elements and a PTN network topology structure; step 3, the input data of the simulation model is determined according to the key indexes; step 4, the input data is inputted to the simulation model to carry out simulation calculation to acquire key index values used for evaluating quality of the PTN network; and step 5, whether the key index values are in a target value scope is determined, if yes, optimization simulation is ended, if not, the simulation model of the PTN network is optimized till the key index values outputted by the simulation model are in the target value scope. Through the method, optimization simulation of the PTN network can be realized.

The invention discloses a power distribution network diagnosis evaluation index weight assignment method based on fuzzy hierarchy and a CRITIC method, and the method comprises the following steps: carrying out the dimensionality reduction classification through employing the regression analysis of factors, removing redundant indexes, and screening out key indexes; performing layered subjective weighting on the screened indexes by using a fuzzy analytic hierarchy process; carrying out objective weighting on the screened indexes by utilizing a CRITIC method; and combining the weights obtained bysubjective weighting and objective weighting based on an optimal combination weight method to obtain the comprehensive weight of the screened index. Diagnostic analysis indexes of the power distribution network are comprehensively arranged, and typical indexes are selected to establish a diagnostic evaluation system, so that subsequent diagnostic evaluation work is facilitated. The power distribution network diagnosis evaluation index weight assignment method based on the fuzzy hierarchy and the CRITIC method can accurately assign the weight to each index, and the accuracy of an assignment result is high.

The invention relates to a city group inter-city railway network construction method. The existing railway network construction method does not consider influences on network planning by regional classification features and hierarchy of the inter-city railway network, and qualitative judgment results are in the majority. The method comprises steps: major railway network nodes are selected; key indexes for reflecting importance of the nodes are selected to construct an importance model, importance of the nodes is calculated, and on the basis, hierarchical division is carried out on the nodes by adopting a cluster analysis method; importance of a connection line between nodes is calculated, node pairs which meet comprehensive contact constraint are screened, line connection is carried out sequentially according to construction urgency, and an initial construction scheme is obtained; and a network construction model is build after network perfection and optimization. A method which combines qualitative analysis and quantitative calculation is adopted to systematically analyze key influencing factors for inter-city railway network construction, quantitative processing on the major influencing factors is realized, and scientific accuracy of the construction result is improved.

The invention discloses a slow-setting polycarboxylic acid water reducing agent and a preparation method thereof. The water reducing agent is prepared from polyether, ammonium persulfate, oxydol, acrylic acid, mercaptopropionic acid, caustic soda flakes, calcium nitrate, sodium nitrite, deionized water and softened water. By optimizing the proportion of the initiator, bonder and other raw materials, selecting chlorine-free deionized water, using higher-dispersibility softened water, simultaneously using the slow-setting polycarboxylic acid water reducing agent, softened water, calcium nitrate and sodium nitrite and optimizing the reaction parameters, the slow-setting polycarboxylic acid high-performance water reducing agent has the advantages in water reducing rate, bleeding rate, gas content, setting time difference / compression strength ratio, shrinkage ratio and other critical indexes. The slow-setting polycarboxylic acid high-performance water reducing agent has favorable use effect and obvious cost advantage, and is worthy of wide-range popularization.

The invention provides a channel engineering ecological environment influence multi-level comprehensive index system architecture. The method belongs to the technical field of ecological environment influence evaluation, wherein the four levels have a step-by-step inclusion relationship; the system comprises four influence process index subsystems, a 15-class influence type index module, 39 sets of impact factor indicators and a plurality of single-factor classification sub-item indexes are provided; an ecological environment influence path based on mechanism analysis and key indexes in mitigation countermeasure evaluation are systematically integrated; the transverse main framework covers the navigation channel project and affects the operation activities of the related areas; living environment change, species activity, ecological influence whole-process action mechanism, influence type depiction is carried out through a longitudinal main framework. Influence factor and single factorclassification item index fine description and analysis are carried out through transverse and longitudinal branch structures, and systematic display of channel engineering ecology influence evaluation results and identification, design, monitoring, investigation, analysis and evaluation of ecological channel construction key indexes are facilitated.

The invention provides a software rejuvenation method based on a multiplicative seasonal model. The method comprises the following steps: determining the aging index of software and extracting a key index value; establishing the multiplicative seasonal model; evaluating ageing conditions according to the multiplicative seasonal model. According to the invention, expressive ability of the multiplicative seasonal model to a seasonal variation tendency is utilized, the relevance of the same periodic points in different periods is considered in actual evaluation, and the relationship of different periodic points in the same period is also considered, so that the method relatively conforms to the actual situation of aging index observed data and the variation tendency of the system key index can be predicted more accurately.

The present invention is production process of surgical gloves of low protein rubber. The low protein rubber gloves are produced on the basis of available surgical gloves producing process via increasing one protein eliminating step, in which the rubber gloves are processed with the protein extracting solution comprising borax, ammonia water and water and through soaking at 60-65 deg.c while stirring for 2 hr, soaking at normal temperature for 22 hr, soaking in clear water for 20-30 min, boiling in water, mixing with powder, tumble-drying and cooling. The said protein eliminating step can lower the protein content by 53.9 % and make the residual soluble protein content lower than the allergic critical index.

The invention provides a transfer learning fault diagnosis model of a distribution transformer. The transfer learning fault diagnosis model is implemented according to the steps of (1) dividing statequantity affecting a running state of the distribution transformer into dynamic state quantity, quasi-dynamic state quantity and static state quantity, and building a running state evaluation index system of the distribution transformer; (2) performing binary quantization on the index state quantity, digging an incidence relation with a fault by an Apriori algorithm, and extracting key index statequantity of inducing a fault of the transformer; (3) introducing a Tanimoto coefficient, and transferring effective auxiliary fault data to a target distribution transformer; and (4) performing iterative solution on weights of target fault data and auxiliary fault data by a transformer learning algorithm TrAdaBoost to obtain a fault diagnosis model of the distribution transformer for fault diagnosis of the target distribution transformer. Auxiliary fault information of the distribution transformer is transferred to the target distribution transformer, and the problem brought to fault diagnosis of the distribution transformer due to a few pieces of single fault data is solved very well.

The invention discloses a power grid self-organized critical state quantitative evaluation method based on the multi-level variable weight theory in the field of power system cascading failure prevention and defense. The method includes the steps that a key index set influencing power grid self-organized critical states is determined; the self-organized criticality of a power grid under each operation state in a sample set is determined; an original physical index set is divided into a physical layer and a factor layer, and the weight of a physical layer index under each operation state in the sample set is calculated on the basis of the positive and negative ideal variable weight theory; the expression and dimensionality of a factor index are calculated on the basis of a principal component analysis method, and it is guaranteed that information of the factor index is not overlapped; a matrix and a principal component information expression factor are judged on the basis of consistency established by physical layer index weights, and the weight of a factor layer index is calculated; by means of the rank-sum ratio comprehensive evaluation method, the factor layer index serves as input, and an estimated value is calculated. The method is capable of comprehensively describing the influence mechanisms of each factor on the power grid self-organized critical states and quantitatively evaluating the self-organized critical states of the power grid, and is high in computation speed.

The present invention relates to a method of electricity forecasting based on the output of industrial chain products, comprising the following steps: 1) Screening industrial chain indicators, and extracting index data, said industrial chain indicators include social overall economic development level indicators and major industry economic development levels 2) Construct the industrial chain index database; 3) Extrapolate the power forecasting model through the above index data and the industrial chain index database. The beneficial effects are as follows: firstly, the present invention comprehensively considers the relevance of various related industries and their industrial chains, screens key indicators that have an impact on the electricity market, identifies deterministic factors such as product output of the industry, and finally reflects the output of related products in the industrial chain. The trend of future power consumption is forecasted.

The invention discloses a transformer performance evaluation method, and solves the problem that subjective factors are taken as a basis to analyze problems and an objective theoretical basis is lacked in the prior art. Firstly, a transformer performance evaluation key index system is constructed, then weights of indexes are obtained through an analytic hierarchy process, finally, a quantitative correction scoring function is introduced to obtain scores of all the indexes and the overall performance of the transformer, the fault condition is analyzed according to the scores, the performance level of the transformer is divided, and the maintenance level is recommended. According to the transformer performance evaluation method, all parts and parameter sources of the transformer are comprehensively considered, the transformer performance scoring function is reasonably given, certain practicability is achieved, and the technical problems that in a transformer performance evaluation system, the number of indexes is large, and the indexes are connected and influenced mutually are solved.

The invention provides a smart home poisonous gas prevention and control system based on the Internet of Things. Indoor poisonous gas can be monitored in real time, when the concentration of the poisonous gas exceeds a critical index, the system automatically executes corresponding prevention and control measures, and thus personnel casualties or property losses are avoided. The smart home poisonous gas prevention and control system comprises a main control center, and further comprises a poisonous gas sensing terminal and an emergency executing mechanism. The main control center is in wireless communication with a switch circuit of the emergency executing mechanism. The poisonous gas sensing terminal comprises at least one of a CO sensing terminal, an ammonia gas sensing terminal and a formaldehyde sensing terminal. The emergency executing mechanism comprises at least one of an alarm, an exhaust device and a window opening device, and further comprises a GSM module in communication with the main control center. The main control center is in wireless communication with the emergency executing mechanism and the poisonous gas sensing terminal through a Zigbee protocol or an IEEE 802.15.4 protocol.

The invention provides a key index determining method and device. The key index determining method includes: determining economic fluctuation impact indexes representing impact on economic fluctuations on the basis of acquired historical economic impact data; using the economic fluctuation impact indexes as independent variables and using economic fluctuation indexes representing economic fluctuation conditions as dependent variables to construct an economic fluctuation impact index screening model; training the economic fluctuation impact index screening model, and selecting a first economicfluctuation impact index set from the economic fluctuation impact indexes; performing further preset screening processing on the first economic fluctuation impact index set to acquire a key index thataffects the economic fluctuation indexes.

The invention relates to an early warning device and method for coal and gas outburst and belongs to the field of technical research of mine instruments and apparatus and outburst-prevention technologies and techniques. The specific working processes comprises the steps that monitoring data of a gas sensor, monitoring data of a wind speed sensor, structure design of a tunneling roadway and coal body industrial analysis parameters are transmitted into a host of the early warning device for coal and gas outburst in real time; through a working face coal body gas analytical mathematical model arranged in a system, the analytical gas content of a tunneling working face coal body in the current position is calculated and obtained; fitting correction is conducted by combining with the gas testing result in a laboratory, and the occurrence condition of original gas of the coal body in front of the working face is obtained in an inversion mode; and then, through an early warning mathematical model arranged in the early warning device and the outburst critical index inspecting result in the laboratory, real-time and continuous operation of the early warning result of coal and gas outburst is realized. The disadvantage that two 'quaternity' is adopted at the present stage, but in the prevention and treatment processes of coal and gas outburst, all-weather, continuous and accurate early warning is difficult to realize is overcome.

The invention relates to a method for quantitatively defining a non-viscous bottom sand starting critical index. under the conditions of certain bed surface bottom sand and variable water flow, a high-speed camera is used for continuously shooting bed surface sediment images; color images continuously shot by the high-speed camera are preprocessed; obtaining the motion state of the sediment particles in each subdomain in the camera shooting area; identifying a moving subdomain in the camera shooting area; defining distribution characteristics of movement of silt in a camera shooting area, counting the sum of areas of all subdomains in which silt movement occurs, calculating the percentage of the subdomains in which silt is started in the camera shooting area, and taking water flow intensity when the percentage of the subdomains in which silt is started in the camera shooting area is 0 as a critical hydraulic index for defining bottom sand starting; According to the method, the bed surface sediment starting critical index can be accurately and quantitatively defined, the problem that the bottom sediment critical starting index is difficult to quantitatively define is solved, and thecritical index determined through the method can be conveniently expanded and applied to bed sediment starting observation under different water and sediment conditions.

The invention discloses a contribution degree identification method of influence factors of dam health conditions in full time and space domains. The method comprises the following steps: (1) defininga dam safety condition as a decision-system condition index, and using a dam overall-safety degree as a decision index to set a calculation parameter lambda and an index contribution degree lower-limit sig_ctrl; (2) calculating a neighborhood radius of a dam health condition index, and acquiring all sample neighborhoods [delta](x); (3) calculating a decision positive-domain POS(D), a dependence degree of the decision index on the condition index and a contribution degree SIG(a, B, D) of the condition index for any dam health status index a which is an element of a set A-red, wherein A-red is an index reduction set; and (6) finding an index a<k> with a highest contribution degree and a contribution degree SIG(a<k>, B, D) thereof, and carrying out judgment to complete identification of the contribution degrees of the influence factors of the dam overall-health conditions. According to the method, a neighborhood rough-set theory is introduced to carry out measurement of the contribution degrees of the influence factor indexes of the dam overall-health conditions to find the key index influencing the safety condition, and analysis of contribution degrees of all measurement-point safety degrees on the dam overall-safety condition is realized.

The invention relates to the technical field of artificial intelligence, and provides a data index screening method and device, computer equipment and a storage medium, and the method comprises the steps of carrying out the standardization processing of user data under a corresponding data index according to data distribution; generating a standard data vector of each user according to the standard data obtained through standardization processing, and extracting multiple pieces of index feature data in the standard data vector of each user; screening a plurality of pieces of first key index feature data according to the correlation indexes of the plurality of pieces of index feature data; extracting a plurality of pieces of second key index feature data and the index weight of each piece of second key index feature data by adopting a minimum absolute contraction and selection operator; and according to the index weight, using a Monte Carlo simulation method to simulate and train the user level prediction model for multiple times, and screening out multiple pieces of target key index feature data from the second key index feature data according to a prediction result corresponding to simulation training. According to the invention, the optimal data index can be screened out, and the screening efficiency of the data index is high.

The invention discloses a zinc oxide field suppression resistance assembly safety assessment method. As an accurate and unified assessment and calculation method based on zinc oxide field suppression resistance site testing data does not exist at present, after the data are measured, the characteristic change degrees and the variation trends of assemblies can only be roughly seen. According to the zinc oxide field suppression resistance assembly safety assessment method, a newly-defined zinc oxide field suppression resistance breakdown voltage safety critical index K is deduced for serving as a judgment basis, the safety critical index is converted into a corresponding safety critical value Kact through the adoption of the maximum assembly field suppression energy and the maximum assembly allowing energy, after the breakdown voltage of the assemblies is obtained through site measurement, only the ratio of the minimum actual measurement assembly breakdown voltage to the average other-assembly breakdown voltage needs to the calculated, and then the ratio is compared with the safety critical value to be capable of obtaining an assembly safety assessment conclusion. By means of the zinc oxide field suppression resistance assembly safety assessment method, the aims of assembly safety calculation and assembly safety assessment after zinc oxide field suppression resistance site measurement are achieved, and the accuracy of the safety calculation and assessment conclusion is improved.

The present application provides a method for monitoring risk of rock burst. The method for monitoring the risk of the rock burst comprises the following steps of: monitoring the support stress of ananchor rod and / or an anchor cable; determining a monitoring index for evaluating the risk level of the rock burst according to the supporting stress of the anchor rod and / or the anchor cable; determining the hazard level of the rock burst according to the relationship between the monitoring index and the critical index of different hazard levels of the rock burst. In the embodiment of the invention, the support stress of the anchor rod and / or the anchor cable is used for the risk analysis of rock burst, and the accuracy of the warning for the rock burst can be effectively improved. Further, according to the monitoring for the rock burst based on the support stress of the anchor and / or the anchor cable, additional drilling operations and interference to the normal tunneling and mining can be avoided, the work efficiency is improved.

The invention discloses a power grid investment strategy benefit comprehensive evaluation method. At present, the research on the power grid investment benefit evaluation is mostly concentrated in thepower market and power generation engineering, the evaluation of the investment benefit of the power grid enterprises is still in the initial stage, and the evaluation of the investment benefit of the power grid enterprises is less effectively integrated with economy and technology, more concentrated in the distribution network and a single project and less research for the power grid enterprises, and cannot measure the investment benefit of the enterprises in an all-round way. The method comprises the steps: 1) measuring and calculating a fuzzy value according to a membership function; 2) after normalizing the fuzzy value of the membership function of the key index influencing the investment strategy, adopting the FCM algorithm to perform clustering; 3) drawing the evaluation grade distribution map; and 4) using the comprehensive weight coefficient method to comprehensively evaluate the investment strategy to be evaluated. The FCM algorithm is applied to cluster the key influence index of the power grid investment strategy so as to further meet the actual application scene.

The invention discloses a method and a device for simply and conveniently detecting strength of building steel. The method comprises steps as follows: a standard sample with qualified known strength is subjected to critical index detection on the detection device provided by the invention, and standard deflection and standard load are determined; a to-be-detected sample is detected with the same method according to the standard load, and whether the strength of the to-be-detected sample is qualified can be rapidly judged through observation of the deformation condition of the to-be-detected sample and a relationship of to-be-detected deflection and the standard deflection. According to the mode, conclusion determination can be realized without quantization of a detection result, the detection efficiency and the constriction efficiency of the steel in the site are greatly improved, and the detection method is fast, effective, economic and applicable.

The invention discloses an industry development business index calculation method, system and device, and the method comprises the following steps: collecting the data of various commercial and tradeeconomic indexes, and carrying out the preprocessing of the data; Analyzing from the commercial economic indexes to obtain key indexes; Calculating a seasonal coefficient according to the index valueof the key index; Estimating corresponding monthly index data according to the seasonal index data; Performing next month data prediction calculation according to the monthly index data to obtain corresponding next month prediction data; And according to the seasonal coefficient of the key index and the next month prediction data, calculating a growth rate prediction value of the industry growth value as the industry business index of the next month. According to the method, the comprehensiveness of the index can be effectively improved, so that the index calculation accuracy is improved. Andthe combination of the calculation indexes can be dynamically adjusted and optimized according to the actual economic situation, so that the calculation result can reflect the current economic situation better. The method can be widely applied to the field of business big data.