256 results about "Statistical index" patented technology

Methods and apparatus consistent with the invention provide the ability to organize, index, search, and present time series data based on searches. Time series data are sequences of time stamped records occurring in one or more usually continuous streams, representing some type of activity. In one embodiment, time series data is organized into discrete events with normalized time stamps and the events are indexed by time and keyword. A search is received and relevant event information is retrieved based in whole or in part on the time indexing mechanism, keyword indexing mechanism, or statistical indices calculated at the time of the search.

Visualization techniques are provided for a clustered multidimensional dataset. A data set is visualized by obtaining a clustering of a multidimensional dataset comprising a plurality of entities, wherein the entities are instances of a particular concept and wherein each entity comprises a plurality of features; and generating an icon for at least one of the entities, the icon having a plurality of regions, wherein each region corresponds to one of the features of the at least one entity, and wherein a size of each region is based on a value of the corresponding feature. Each icon can convey statistical measures. A stabilized Voronoi-based icon layout algorithm is optionally employed. Icons can be embedded in a visualization of the multidimensional dataset. A hierarchical encoding scheme can be employed to encode a data cluster into the icon, such as a hierarchy of cluster, feature type and entity.

The invention relates to a big data-based social insurance index warehouse building system and method and belongs to the technical field of big data application. The invention aims to build an accurate and regularly-updated multi-dimensional statistical index base based on the organization of cubic structure storage by using the big data processing technology and distributed storage technology. The building system consists of a data source module, a business data collection module, a data pretreatment module, an index calculating module, an index metadata storage module, a data storage module and a data query module. The building method is based on the building system. The system and the method uses social insurance business data as the data source and builds an accurate and regularly and incrementally-updated index data warehouse by using the big data processing technology and distributed storage technology, and allows rapid index multi-dimensional analysis and query.

The invention discloses a spatial visualization revealed two-dimension code food information tracing method which comprises generating enterprise terminal two-dimension code labels comprising food quality and safety information and producing area geographic positions; adopting a label recognizer with a global position system (GPS) to scan two-dimension code labels in food storage, transportation and sale links, storing obtained geographical coordinates and link information in a data base and generating retail terminal two-dimension code labels; conducting statistics and platform building: adopting a statistic geographic information system (GIS) TO analyze and process data and building a visualization food information exhibiting and inquiring platform; and tracing: scanning the enterprise terminal two-dimension code labels and / or the retail terminal two-dimension code labels by using a mobile terminal and obtaining corresponding label information. The method enables statistical indexes to be overlapped and displayed on an electronic map, achieves perfect combination between statistical information and geographical location information, reveals food quality safety information in a visual mode and provides and effective mode for collection, statistics and analysis of safety food information.

The invention relates to a quality evaluation method of electricity statistical index data. The method comprises the following steps: obtaining to-be-evaluated electricity statistical index data according to the requirement of an actual evaluation purpose; choosing corresponding data quality evaluation indexes; making data quality evaluation rules corresponding to the data quality evaluation indexes; calculating the weight Wi of a quality evaluation index Ii, and setting an expected value Ei; performing detection and analysis on quality evaluation indexes of the statistical index data, and calculating the percentage Si of data that meets the quality evaluation index Ii; according to the weight Wi, the percentage Si and the set expected value Ei, respectively calculating the comprehensive evaluation value SA, the overall expected value SE and the relative difference SR of the statistical index data, and performing evaluation on the overall quality of the statistical index data according to defined evaluation grades; and processing evaluated unqualified statistical index data. The method provided by the invention can be applied to quality evaluation of electricity statistical index data in the power industry.

The invention provides a thermodynamic diagram showing method and device. By adopting the embodiment, a showing ratio of a target image is obtained and thermodynamic parameters are further obtained according to the showing ratio so that a thermodynamic diagram corresponding to the target image is shown according to statistical index data of the target image and the thermodynamic parameters; the thermodynamic diagram is shown by adopting the thermodynamic parameters corresponding to the showing ratio of the target image, so that the problems in the prior art that set thermodynamic parameters are adopted so that a distribution condition of the statistical index data of the target image can not be clearly shown by the thermodynamic diagram can be avoided, and thus, the showing reliability of the thermodynamic diagram is improved.

The invention relates to the technical field of network maps and space information service, in particular to a method for dynamically constructing an online thematic map. The method comprises the following steps of: constructing a sequenced mapping among three sets, namely a statistical index, a visual variable and a map sign by performing online organization and dynamic modeling on heterogeneous distributed statistic index data by a method for drawing a multi-variable map so as to integrate to form a drawing rule set in which a gathering visual variable is used as a core characteristic; and formalizing description language by using extensible markup language (XML) as a network map sign, dynamically constructing a personal thematic map by using a format of a network thematic map service combination, and forming the online thematic map in a logic layer model organization of a map group, a map picture and an illustration, which is detailed step by step. By the method, a map expression acquired by the user comprises dynamic customization expressed in the forms of a map sign, a color and the like, so the humanized requirement of the map user can be fully met; and aiming at users on different levels, the thematic maps meeting the service requirements can be designed, and the effect is remarkable.

The invention discloses a Chinese emotion new word recognition method and system in combination with user emotion expression ways.The method includes the steps that input texts are acquired; a candidate new word set is established based on character strings, with word frequencies larger than that of a first preset threshold value, in the input texts; the candidate new word set is filtered through a Chinese old word library; new words are screened out of the filtered candidate new word set based on statistical indexes, and a new word set is established, wherein the statistical indexes include word formation ability, pointwise mutual information, flexibility and adjacency entropy; based on the emotion tendency pointwise mutual information, emotion new words are recognized from the new word set, and an initial emotion new word set is established; based on the user emotion expression ways involved in the input texts, high-confidence-coefficient emotion new words are screened out of the initial emotion new word set to serve as recognized Chinese emotion new words.By means of the embodiment, the technical purpose about how to improve the precision and flexibility of emotion new word recognition is achieved.

The invention belongs to the field of computer natural language processing and relates to a method for discovering compound words in a specific field based on statistics and rules. The method comprises the steps as follows: carrying out word segmentation and part-of-speech tagging by a word segmentation system, traversing word segmentation results, filtering by stop words and word-formation rules, traversing to generate a digraph of atomic words, permutating and combining possible compound word combinations by depth traversal, restricting by statistical indexes and the word-formation rules at the same time, generating a compound word candidate set for manual screening, and importing the compound words into a dictionary file for later use. The method has the advantages as follows: the digraph of the atomic words is created, and the compound word boundary is automatically sought by the depth traversal, so that the compound word with any length can be identified; the word-formation rules are convenient to customize and expand and good in portability; higher accuracy and recalling rate are obtained at the same time, so that the Chinese word segmentation accuracy is improved; and the generated compound words can have more accurate concepts, so that a good foundation is laid for a deep research on Chinese information processing.

The invention discloses an intelligent power grid false data injection attack detection method which combines a variational mode decomposition technology and a machine learning technology. The detection method is added behind a power system state estimation part, and comprises the following steps: firstly, decomposing a system state time sequence into a set of a plurality of sub-sequences with different center frequencies by using a variational mode decomposition technology; secondly, in order to compress redundant data to facilitate model training, expressing data segment characteristics by using characteristic quantities based on statistical indexes; and finally, constructing a false data injection attack detector under the smart power grid by taking the calculated feature set as a training set of an online sequential extreme learning machine. In the process, the credible authenticated data can be used as an extended training set to continuously optimize the performance of the detector with the online learning capability. The invention aims to establish an efficient and accurate false data injection attack detection method for the smart power grid to ensure safe control and stable operation of a power system.

The invention discloses a time domain self-correlation Nakagami-m fading complex channel simulation method, which comprises the steps of: firstly, carrying out independent simulation on envelope distribution, so that a probability density function and a cumulative distribution function of envelopes are consistent with theoretical values; secondly, carrying out independent simulation on phase distribution, so that statistical indexes of a probability density function and a cumulative distribution function of phases are consistent with theoretical values; then ranking an envelope sequence and a phase sequence, so that a self-correlation function and a power spectral density are consistent with theoretical values; and finally, superposing the ranked envelope sequence and phase sequence to obtain a time domain self-correlation Nakagami-m fading complex channel random sequence satisfying all simulation performance evaluation statistics. The time domain self-correlation Nakagami-m fading complex channel simulation method realizes good self-correlation characteristic fading simulation and fast fading simulation of a time domain self-correlation Nakagami-m fading complex channel, has good extensibility, and brings convenience for subsequent adoption of a more efficient module simulation algorithm.

The invention provides a graphical model full-life-cycle modeling method for federated learning, which comprises the following steps: analyzing a data sample before modeling, and determining a federated learning scheme; drawing up a modeling strategy according to a joint analysis operation result; adopting a dragging mode and using a federation feature engineering means to process the data; in thefederated model training process, after the two parties construct models respectively, exchanging an intermediate state model and a loss function which are obtained through calculation ; predicting and using the federated model; and monitoring the operation process of the federated model to obtain a model monitoring statistical index so as to realize maintenance iteration of the federated model.Personnel in each step of federated learning modeling can participate in optimization points through imaging, the personnel participation optimization difficulty is reduced, a later model applicationmaintenance way is provided, and the application scene and usability of the federated learning technology are improved.

The invention belongs to the field of research of solar energy utilization, and in particular relates to a longitudinal photovoltaic power prediction method based on historical data mining. The longitudinal photovoltaic power prediction method comprises the steps of: performing statistical analysis for historical photovoltaic power data in different seasons at first, so that six statistical indexes of photovoltaic power in corresponding seasons are obtained; clustering the statistical indexes by utilizing the Euclidean distance, so that similar day matrixes under different weather conditions in different seasons, and forming similar day typical curves and distribution intervals through a one-dimensional forward cloud generator; realizing longitudinal photovoltaic power prediction at the corresponding times in 24 hours in the future by utilizing the Markov Chain theory, and fusing the prediction value with the similar day typical curves and distribution intervals, so that a new prediction value is formed; and finally, performing weighted fusion of the new prediction value and the prediction value obtained through a continuous prediction method through a one-dimensional reverse cloud generator. Thereby, longitudinal photovoltaic power prediction based on historical data similar cloud fusion is realized; and thus, the photovoltaic power prediction precision is further increased.

The invention discloses a method for the health diagnosis of a concrete bridge structure based on statistical indexes, which comprises the following steps of: for each flexibility measurement point, only retaining four data of a maximum value, a minimum value, a starting value and a finishing value of monitoring data every day and calculating an ADX index, a DMA index and a TRIX index according to the retained data; (1) describing the current deterioration trend of the bridge structure by adopting the ADX index; (2) describing the intermediate-term and short-term deterioration trends of the bridge structure by adopting the DMA index; (3) describing the long-term deterioration trend of the bridge structure by adopting the TRIX index; and (4) according to the calculation result of the three statistical indexes, obtaining an ADX index value, a DMA index value, an AMA index value, a TRIX index value and a TRMA index value, drawing the combination of various index values into a structure safety evaluation diagram on the same coordinate system and carrying out comprehensive evaluation on the health state of the bridge structure. The invention has the advantages of providing a method for the non-model evaluation of the safety of the bridge structure and avoiding the storage and processing of mass data.

The invention discloses a configurable heterogeneous data real-time synchronization and visualization system and method, and the system comprises a meta-bin subsystem module which stores historical and real-time incremental meta-data information; a historical data batch processing synchronization subsystem module which is used for acquiring and processing historical metadata information and storing the historical metadata information in a preset data warehouse in a preset format; a real-time synchronization subsystem module which is used for acquiring real-time incremental metadata information, processing the real-time incremental metadata information to complete data type conversion and storing the real-time incremental metadata information in a preset data warehouse; a visual large screen subsystem module which is used for carrying out configuration management on data and user-defined statistical indexes in a preset data warehouse and the visual large screen; And a visualization module which is used for displaying the data on a large screen for a user to check and manage. The system can combine real-time data flow in a big data warehouse Hive with a statistical analysis task in aself-defined statistical index form, is bound with a real-time big screen, and provides a solution of data from an online business system to big data statistical analysis.

The embodiment of the invention discloses a service monitoring system and method. The system comprises a data acquisition module, a monitoring data processing module, a log data processing module and a computing engine, the data acquisition module is used for acquiring service operation basic data and dividing monitoring data and log data from the service operation basic data; the monitoring data processing module is used for acquiring monitoring data and counting the monitoring data according to a preset statistical index to obtain a corresponding monitoring result; the log data processing module is used for acquiring log data and generating a topological graph corresponding to the single service request according to the log data, and the topological graph is used for representing a background module calling relation responding to the single service request; the calculation engine is used for obtaining a monitoring result and a topological graph and determining whether the background module has a fault or not according to the monitoring result and an alarm threshold value corresponding to the statistical index; under the condition that a fault exists, the reason of the fault is accurately positioned according to the monitoring result and the topological graph.

The invention discloses a harmonic responsibility quantification method based on a harmonic analysis integrated equivalent circuit and belongs to the field of a harmonic responsibility quantification technology. Apart from an evaluated user, other parts of a power grid are taken as a system; an attention period of harmonic responsibilities is divided into N analysis periods; obtaining fundamental waves, subharmonic voltages and harmonic current phasors of N+L-1 analysis periods are obtained by acquiring bus voltages and current waveforms at a common connecting point between the system and the evaluated user of the attention period and L-1 analysis periods before the attention period; an equivalent circuit model in which a harmonic voltage source at a system side is connected in series with harmonic impedance and an equivalent circuit model in which a harmonic current source at a user side is connected in parallel with the harmonic impedance under h-time harmonic waves in k-th analysis period are established; an h-th harmonic analysis integrated equivalent circuit in the k-th analysis period is obtained; and when K is greater than and equal to N+L, harmonic responsibility quantification statistical indexes at the system side and the user side in the attention period are obtained. According to the invention, the harmonic responsibilities of the system side and the user side are more clearly defined, and application in engineering practice is facilitated.

The invention discloses a quantitative evaluation method of the arc welding process stability based on an electric arc sound. The method concretely comprises the steps of: carrying out short-term energy calculation on a de-noised electric arc sound signal, drawing a probability cumulative distribution map and a probability distribution histogram by utilizing a statistical index; calculating the stage slope of a probability cumulative distribution curve and a probability distribution maximal value of energy, and finally achieving welding process stability evaluation through the designed electric arc sound evaluation index (ASST). According to the invention, short-tem energy and a statistical theory are combined to design a welding process stability evaluation system of the electric arc sound; two situations of distribution and variation trend of the electric arc sound energy are comprehensively considered, and the welding process stability evaluation index based on the short-term energy is automatically designed. According to the method disclosed by the invention, the stability degree of the arc welding process can be effectively quantified by the electric arc sound.

The invention relates to a method for real-time power prediction of photovoltaic power station based on a SAGA-FCM-LSSVM model, which includes collecting power generated in corresponding period of time of photovoltaic power station and corresponding meteorological parameters on meteorological station, and obtaining meteorological data; power parameter samples of the daily weather being pretreated;based on four statistical indexes and simulated annealing genetic algorithm, the fuzzy C-mean clustering algorithm clustering the samples from the first day of the history day to the day before the forecast day. According to the meteorological eigenvalue of each cluster sample set, the center point of each cluster meteorological eigenvalue is calculated, and the classification of the forecast date is judged by Euclidean distance. The least square support vector machine is trained by using the same kind of parameter samples as the predicted date, and the training model is obtained. The meteorological parameters and power values of the first 2 hours of the time to be predicted are input into the training model for real-time prediction of the power generation at each time of the time to be predicted. The invention can predict the output power value of the photovoltaic power station at each time in real time.

The invention relates to an electric power multi-objective decision support method based on an intelligent data mining model. The method comprises the steps of enabling a decision maker to be clear on decision objectives and determine objective layers according to properties of practical problems; calculating all influence factors needing to be considered to achieve the objectives, performing induction and synthesis on the influence factors, and determining criterion layers; adopting a frequency statistical index screening method to perform mass election on all indexes under every criterion layer, and deleting indexes from which observed data cannot be obtained according to an observability principle; adopting the sum of deviation squares to cluster the indexes in every criterion layer; adopting a factor analysis method to analyze factor loads of every statistical index, reserving indexes with maximum factor loads in every kind of indexes, and screening out co-factor indexes between the multiple criterion layers; establishing decision models between indexes layers and the criterion layers on the basis of a multivariate regression analysis method; searching optimal balancing points between multiple criterions according to decision models of every criterion so as to achieve optimum of a final objective layer.

The embodiment of the invention provides a data processing method and device and electronic equipment. The method comprises the steps that label data in a label data set serve as input, unintentionaltransmission with first equipment is conducted, target sub-data are selected from multiple sub-data input by the first equipment, and the multiple sub-data are obtained based on splitting parameters in a splitting parameter set; the selected target sub-data is summed to obtain a first summing result; a second summation result sent by the first device is received, wherein the second summation result is obtained by summing splitting parameters in the splitting parameter set; and a statistical index is calculated based on the first summation result and the second summation result. According to the data processing method and device and the electronic equipment provided by the embodiment of the invention, each data party can jointly complete data index statistics on the premise of not leaking data owned by the data party.

The invention discloses an online monitoring method for insulation of a three-phase asynchronous alternating current motor stator. The online monitoring method comprises the following steps of synchronously collecting voltage and current signals of a motor insulation system; using a PWM (pulse width modulation) demodulation technique to process the collected voltage and current signals of the motor; extracting feature indexes of the processed signals, such as a MCSA (motor current signature analysis) feature index, a current signal statistical mode identification index, a sequence voltage distribution statistical index, a Park conversion feature index, a three-phase alternating current voltage difference statistical index and a three-phase alternating current difference statistical index; using each extracted index as a training set of a support vector machine to pre-diagnose the state, outputting the comprehensive state pre-diagnosis result of the motor insulation system, and evaluating the running state of the motor insulation system on line. The online monitoring method for the motor insulation system has the advantages that the motor insulation state can be effectively monitored for a long time; by integrating multiple types of insulation feature indexes, the reliability and monitoring precision of the method are improved, and the data processing precision is high.

The invention relates to a data management and statistical analysis commercial intelligent platform. According to the platform, standard processing is performed on statement data of a user through a standard basic form, and after calculation is performed through a designed calculation formula and a model, the statement data is displayed to the user in a figure and table form through a standard statistical index system; the user pertinently does daily management improvement work through a standard statistical index calculated based on basic data of a current company; or, the user presets a threshold corresponding to the index and an execution instruction, and after the index reaches the threshold, the platform automatically executes the preset instruction or pushes prompt information to theuser, so that semi-automatic or automatic operation of daily operation management of the company is realized. Through the platform, the working efficiency of daily operation management of the companyis improved, a company operation management risk is timely discovered and avoided, company operation management cost is lowered, and the profitability of the company is improved.

The invention relates to an electric power statistical index relevance analysis method which breaks away from an inherent thinking mode of traditional statistical index relevance analysis. The method includes the steps: analyzing relevance of electric power statistical comprehensive indexes by the aid of relevance analysis theory and analyzing correlation of the indexes; finding the causal relationship among the indexes and a core index by introducing linkage analysis theory in econometrics to determine key indexes of the core index; and finally, establishing a relevance model for the electric power statistical core index and the key indexes to obtain the sensitivity coefficient, quantizing the correlation and determining the dependence and affection degree of the indexes to form an electric power statistical index system articulation graph by taking the core index as a center. Compared with a traditional method, the electric power statistical index relevance analysis method has the advantages that correlation of the statistical indexes can be more visually and comprehensively known, and visual, clear and effective support is provided for a decision maker.

The invention relates to the field of data processing technology and discloses a statistical index data processing method and a device; the method comprises the following steps: statistical results are calculated in advance aiming at different organization units and statistical indexes and are stored; when a statistical statement is needed to be viewed, the corresponding data is extracted from the stored statistical results; the statistical statement is generated according to the extracted data; the generated statistical statement is shown. By adopting the invention, the showing speed of the statistical statement can be effectively improved.

The invention discloses a rapid statistics task generation system and method suitable for big data. The method comprises the steps that after a data source adapter, an atomic counter, a statistical indicator generator, a dimension selector, a report generator, a scheduler and a code generator are generated, codes of a statistics task are automatically generated, and when a preset scheduling condition of the scheduler is satisfied, the codes are automatically executed. According to the rapid statistics task generation system and method suitable for the big data, the statistics task is decomposed and defined as the parts such as the data source adapter, the atomic counter, the statistical indicator generator, the dimension selector, the report generator and the scheduler, when a user creates a task of the user, the user can drag the indicators needed by the user, and then statistics codes are automatically generated according to a standard model configured by the user. Accordingly, the complex cloud calculation process is simplified, module componentization is achieved, the statistics task codes are rapidly generated, the development efficiency is greatly improved, and the rapid statistics task generation system and method suitable for the big data can be widely applied to the big data statistics industry.