2992 results about "Data platform" patented technology

The invention relates to an information system integration method for power network manufacture control macrozone and management information macrozone which belongs to the technical field of power network control and management systems. The method includes coding for power network devices uniformly; a comprehensive data platform is established, consisting of a first data platform and a second data platform arranged in the power network manufacture control macrozone and the management information macrozone; the model, graphs and real time data as well as historical data of the power network manufacture control macrozone are transmitted into the first data platform and stored into a first data platform database; a mirror image of the first data platform database is set up on the second data platform; the management information data of the power network management information macrozone are transmitted into the second data platform; the first data platform database and the management information data are integrated and then displayed by the second data platform carries out conformity. The method practically realizes the integration on the information systems of the power network manufacture control macrozone and the management information macrozone, thereby improving the information using efficiency of each system of the power network and promoting the automatization of the power network dispatching and the information management level.

An advanced intelligence engine (AIE) for use in identifying what may be complex events or developments on one or more data platforms or networks from various types of structured or normalized data generated by one or more disparate data sources. The AIE may conduct one or more types of quantitative, correlative, behavioral and corroborative analyses to detect events from what may otherwise be considered unimportant or non-relevant information spanning one or more time periods. Events generated by the AIE may be passed to an event manager to determine whether further action is required such as reporting, remediation, and the like.

The invention relates to a drilling well control parameter intelligent monitoring system which comprises a monitoring part for drilling fluid cycling volume, a monitoring part for drilling fluid inlet and outlet flow, a monitoring part for drilling fluid inlet density, outlet density, drilling temperature, outlet natural gas, and H2S concentration, a monitoring part for wellhead pitshaft flowing fluid level and table torque, and a collection instrument part. All the signals are transmitted into the collection instrument to be collected through an RS485 network cable; after data processing is carried out, the data is transmitted to a drill floor parameter display device and a central station host computer through a wireless data transmission device; the data storage, display and print are carried out by the host computer, and the data is simultaneously uploaded into a data platform processor of an upper-level command center; finally, remote control realtime processing and monitoring are carried out on all the well control parameters of all the drilling crews. The intelligent monitoring system has the beneficial effects of realizing omnibearing, long-distance and timely drilling well control, safe production, and playing better role in preventing the occurrence of accidents such as well kick, loss circulation, blow-out, etc.

The invention discloses a big data mining based integrated forest fire prevention informatization system. The big data mining based integrated forest fire prevention informatization system comprises a big data platform, and a multi-dimension perception subsystem, an early-warning prediction subsystem and a multi-hierarchy application subsystem, which are connected with the big data platform, respectively; the multi-dimension perception subsystem is used for acquiring various forest data, the big data platform is used for pre-processing and computing the data; the early-warning prediction subsystem can realize fire warning and prediction and forest fire spreading prediction; and the multi-hierarchy application subsystem is used for realizing forest resource planning, forest fire prevention management, and forest fire suppression dispatching and command. The big data mining based integrated forest fire prevention informatization system can realize multi-azimuth comprehensive monitoring on a forest, is used for mining and analyzing historical data and mass forestry data obtained by real-time monitoring to accurately predict forest fire and provide an early-warning function, can analyze the development tendency of the forest fire to provide aid in decision making, can put out the forest fire in an airland and multi-method manner, and can provide high-efficiency and accurate equipment and personnel assignment; and the system is integrated and has high informationization degree.

The invention discloses data exchange and sharing technology among heterogeneous systems. Data and services in different systems can be accessed in a uniform mode. The data exchange and sharing technology can be implemented by the following steps of: 1, establishing an import data source; 2, establishing a data format template; 3, defining a transformation rule; 4, archiving the data format template; 5, importing the data; 6, exporting the data; 7, transforming formats; 8, sorting the data out; 9, recovering the data; 10, encrypting/decrypting and compressing/uncompressing the data; and 11, managing messages. The invention provides a data interface mechanism, enterprise-level data interaction in the systems can be realized by the mechanism, data exchange and sharing of each management system can be realized through an enterprise data platform, and a large number of memory spaces are not required when the data are processed, so that investment in memory equipment can be reduced; and data processing and transmission are performed on line without manual intervention, so that maintenance cost can be reduced.

The invention puts forward a Spark-based big data hybrid model mobile recommending method comprising four steps as follows: firstly, getting a user's commodity purchase data at a mobile end; secondly, extracting user historical data from a database and importing the user historical data to an HDFS, and extracting features, such as user behavior features, brand features, user's personal consumption features and cross features; thirdly, packaging a hybrid model on a Spark platform using an RDD operator, and embedding the model interface into a big data platform for calling; and fourthly, calling the hybrid model interface to extract feature data, setting training parameters of the model, and training the hybrid model. The model is estimated using a test data set and optimized, the trained hybrid model is saved, and relevant recommendation is made. The method can effectively improve the efficiency of recommendation under the condition of a larger amount of data and higher data sparseness.

The invention discloses a data control method based on data platforms. The data control method includes: (1) acquiring data of a plurality of the data platforms and integrating the data, wherein the integrated data includes user data of the data platforms, original data of data items, multi-dimensional descriptions of user behavior, multi-dimensional descriptions of the data items, online data and offline data; (2) processing the integrated data in a distributed processing frame mode and performing normalization operation, standardization operation and data cleaning operation, wherein the normalization operation refers to performing normalization operation to numerical data, the standardization operation refers to organizing the data in structuralization, keeping the data integrity, reducing redundancy and increasing the uniformity of the data, and the data cleaning operation refers to perform the data cleaning operation to incomplete data, wrong data and repeated data; and (3) extracting the processed data and displaying the data. The data control method based on the data platforms improves the speed of data searching through a novel data control mode.

The invention provides a block chain safety storage method. The method makes each client-side Client have a name node, the data storage safety of a big data platform is greatly improved, the pressure brought by a centralized server is effectively avoided by adopting decentration design, and common apportion is performed through a whole privately-owned block chain network; Data Node of each data block of Hadoop is encrypted, and the safety of each data in big data is fully guaranteed. A data storage and management mechanism of the big data platform is further improved, a single mode relying on a central node is converted into a network environment jointly maintained jointly by all participants, and the decentration design is really achieved. By setting PKI and user permission, the shortcoming of simple and extensive plaintext storage of important data is broken through, and a safe and encrypted storage process and method are deepened.

A real time monitoring system and a method thereof of an optical film manufacturing process are provided. The real time monitoring system includes a plurality of production systems and a cloud big data platform which connects to the plurality of production systems. The process data of the production line is collected by as production line data collector of the production system. The process data is uploaded to a database of the cloud big data platform. The historical process data across the plurality of production systems can be combined as a process waveform feature by a profile database. A processor connects to the database and the profile database. The differences between the process data and the process waveform feature are compared in real time. When the difference value exceeds a threshold value, an abnormal message is sent to the corresponding production line.

The invention provides a client, a server side, methods and an authentication system. The client for generating a verification code comprises a transaction initiation unit, a verification code generation unit, and a sending unit. The transaction initiation unit is configured to respond to a predetermined authentication event of a user to initiate a random transaction between a first account and a second account in a data platform system, so that the random transaction is recorded into the data platform system. The verification code generation unit is configured to generate a verification code for authentication of the user at least based on information of the random transaction. And the sending unit is configured to send the generated verification code to a server side, so that the server side verifies the identity of the user based on the record of the random transaction and the verification code. The data platform system is a decentration type distributed database and records in the system can not be changed or deleted. According to the embodiment of the invention, with the data platform system based on a block chain, the user initiates verification code generation actively, so that the system safety is improved and the system cost is lowered.

The invention discloses a method based on police affair big data center service construction. Through building of a police affair cloud data service layer, functions of data collection, data arrangement, data sharing and data analysis are realized, and the police affair cloud data service layer includes a data recourse sublayer, a service resource sublayer, a resource application sublayer, a data sharing platform and a big data platform. According to the method provided by the invention, through building of the police affair cloud data service layer, the functions of all police data collection, data arrangement, data sharing and data analysis are realized, the capability and level of technical service assurance of data processing and data sharing of a public security organization are comprehensively improved, a data mining and analysis capability is perfected and improved, and open and efficient data sharing application and data analysis and mining services are provided for all the police.

The invention discloses a machine learning device, a machine learning method based on the machine learning device, and a big data platform using the machine learning device and the machine learning method thereof. The machine learning device comprises a user-defined process module, a configuration module, a database and an event server, wherein the user-defined process module comprises a logic module, the logic module can receive an executable file contained in a request initiated by a user, and can be called by the event server; and the database binds a front-end development application with the executable file through a configuration file written by the configuration module. According to the machine learning method, the machine learning device and the big data platform, the service logic component is completed by means of the user-defined process module, the adaptability and universality of the machine learning method, the machine learning device and the big data platform for various application scenarios are realized, efficient operation of data mining and machine learning involved in the development process of standardized big data are achieved, the development process of the standardized big data is simplified, and the development and deployment efficiency of the standardized big data is improved.

The invention discloses a Spark-based log auditing and reversed checking system for big data platforms, and belongs to the field of big data and information security. The Spark-based log auditing and reversed checking system comprises a log acquisition module, a log auditing and analyzing module, a log auditing and reversed checking module, a log offline mining module and a view module. Log information in an organization system is acquired by the log acquisition module and is pushed to the log auditing and analyzing module in real time, and the log auditing and analyzing module analyzes the log information in real time, generates warning information and transmits the warning information to front-end pages of the view module. Compared with the prior art, the Spark-based log auditing and reversed checking system has the advantages that the warning information can be analyzed for service staffs in detail, and the Spark-based log auditing and reversed checking system is excellent in practicality and has excellent popularization and application value.

The invention relates to a generalized battery management system for energy storage of new energy vehicles and batteries and provides a generalized battery management system of combining a local battery management system and an offline state evaluation system which runs on a remote big data platform, wherein the local battery management system detects battery parameters (a voltage, a current, a temperature and charge-discharge capacity) in real time, estimates the battery state according to the detected battery parameters, judges whether an abnormal state appears or not, achieves local real-time charge-discharge management and uploads the detected battery parameters to the remote big data platform; and the offline state evaluation system runs on the remote big data platform, estimates the health state of the battery and carries out risk pre-warning according to the historical battery parameters stored in a database and the real-time battery parameters, resets charge-discharge control parameters according to the health state of the battery, dynamically updates a management strategy, gives battery maintenance information and transmits the result to the local battery management system.

The invention provides a cloud-computing-based parking lot management system which comprises a vehicle information collecting subsystem, a thread management subsystem, a resource allocation subsystem, a cloud equipment subsystem, a mobile network interface subsystem and an automatic control subsystem. The could-computing-based parking lot management system can realize interaction with an intelligent cellphone client side, a cloud computing platform is taken as a processing architecture, a big data platform is taken as an information basis, resource distribution, data processing and request response are performed on the basis of service threads, efficient distribution and reasonable utilization of resources are realized by dividing static and dynamic service threads, own running laws of a parking lot are fully met, and high instantaneity requirements on service in the process of traveling can be met. The cloud-computing-based parking lot management system is supportive of a series of intelligent application scenes like parking space vacancy prediction inquiry, parking space optimized selection, incoming and outgoing path planning, vehicle collecting navigation and mobile payment of parking fee.

The invention discloses a distributed network security event associated analysis method based on a knowledge graph. The method specifically comprises the following steps of 1, building a network security knowledge graph comprising five dimensions such as the basic dimension, the loophole dimension, the threat dimension, the alarm event dimension and the attack rule dimension; 2, designing a security event implementation associated analysis algorithm based on the knowledge graph built in the step 1; and 3, building a real-time big data analysis platform, applying the associated analysis algorithm designed in the step 2 to the built big data platform, and thus achieving a distributed associated analysis system. According to the method provided by the invention, related technologies of current big data process are fully used for dealing with the large data volume, the associated analysis algorithm is parallelized, and the design of the distributed associated analysis algorithm based on the knowledge graph is achieved.

The invention provides an OLAP multi-dimensional analysis and data mining system. The system comprises a data model, a distributed OLAP engine, an OLAP analysis engine, a multi-dimensional report analysis interface, a data mining interface and a data visualization tool; the data model is dragged by a user through a visual interface to finish data modeling, and has unified model configuration; thesystem automatically performs model adaptation and enables the data model to be called by cooperation with internal other engines or tools; the distributed OLAP engine provides a multi-dimensional data model preprocessing capability for the OLAP system; the OLAP analysis engine supports a multi-dimensional query analysis engine of a big data platform and a relational database, and analyzes an MDXstatement to obtain a standard SQL; the multi-dimensional report analysis interface and the data mining interface have multi-dimensional data analysis and data mining functions and provide a report analysis method and a data mining algorithm model; and the data visualization tool provides a visual service for report analysis and data mining in the multi-dimensional report analysis interface and the data mining interface, and provides visual result social sharing and chart management functions.

The invention discloses a distributed service management system with elastic expansion and a method thereof. The system has core capabilities: a high-performance RPC framework design, a distributed transaction compensation mechanism, a universal service registry center, a service matching strategy based on a comprehensive evaluation method, and an automatic interface module injection mechanism and the like. Data services of a Large-scale distributed system and a large data platform are provided based on the method. The system is composed of a service issuing component, a service registry center for realizing service discovery and configuration of a distributed system, and a programming model for realizing a user request data universal function based on a layered structure. The linear expansion and high concurrent access capabilities are powerful; full-stack monitoring, tracking, and service state monitoring capabilities are realized; and the architecture, elastic expansion and reliability are greatly improved.

The security enhanced data platform is comprised of two primary subsystems and a host of supporting subsystems. The first primary subsystem is a document management system. A set of client side tools provides the user a way to specify classifications and compartments for selected areas of a document, and a way to save the document in the format required by the system in order to allow the system to enforce the rules and privileges dictated to the system. The second subsystem is a security enhanced database management system. In documents the system allows different user privilege requirements on the document as a whole as well as on pages, paragraphs, sentences, words, and/or letters of a word. A history of document changes is maintained to provide an audit trail after the fact of who did what changes, where those changes were made and when those changes were made.

The invention, which belongs to the data processing technology, discloses a method for constructing a big data platform of government affairs. The method comprises; step one, carrying out an information resource catalog carding analysis: to be specific, carrying out information carding and a relevance analysis of information to form an information resource directory and information demanding and sharing; step two, carrying out government affair big data collection and integration; to be specific, according to the information resource directory, carrying out collection and integration of data resources to form a government affair big data set; step three, carrying out sharing and exchanging of government affair big data; to be specific, carrying out exchanging and sharing between government affair big data; and step four, carrying out an application service of the government affair big data; to be specific, building an application model, digging effective information, and pushing the effective information on needs. The method has the following advantages: government affair data can be dug, analyzed, integrated, and applied effectively and thus integration of electronic information and geographic information technologies can be realized, so that promotion and application of the smart city concept can be realized.

The invention discloses a blockchain big data business information analysis system. The system comprises a business information data platform, a web crawler system, a blockchain storage system, a cloud computing center and a user display side, the business information data platform and the web crawler system are subjected to information interaction, the blockchain storage system stores interaction information, the cloud computing center calls data from the blockchain storage system and processes the data, and a user transmits data processed in the cloud computing center to the user display side by operating the user display side; the business information analysis platform provides first-hand, special, detailed, accurate and personalized business information for the user in the first time. The system can be used in the fields of precision marketing, investment risk control, industrial economy development situation prediction, stock market prediction, enterprise credit evaluation, science and technology project application, market opportunity finding, automatic public opinion monitoring and the like.

A system and method for data replication for databases using an intermediary server, the intermediary server choosing the order in which databases are replicated, the utilities used for each of the steps in the data replication process, the timing of the replication, and/or the timing each step of the data replication process is performed.

The invention relates to a monitoring system of a large data platform. The monitoring system of the large data platform comprises a large data platform operation information statistic module, a large data platform operation monitoring module and a large data platform operation statistic analysis module. The monitoring system of the large data platform resolves the following problems that firstly, the large data platform uses the Hadoop to store and manage data; secondly, for operation on the platform, the large data platform only stores the final state of operation, the middle state of operation is not recorded, and operation analysis is not facilitated; thirdly, the large data platform is lack of statistics and analysis of the operation state and trend, and only the current operation information can be obtained. The monitoring of assemblies in the platform is realized and displayed on an interface. The monitoring system of the large data platform realizes operation middle process monitoring, and collects and stores the input and output data amount and dependence information of operation. Through statistics and analysis of data in the operation process, the monitoring system of the large data platform realizes statistics and analysis of the operation trend in the large data platform.

The invention discloses a wireless sensor network system for monitoring real-time data of a power grid, which comprises a wireless sensor node, a gateway node, an Internet network and a monitoring center data platform, wherein the wireless sensor node is used for collecting real-time running state parameters of power grid equipment and transferring the collected parameters to the monitoring center data platform through the gateway node and the Internet network; the monitoring center data platform is used for monitoring the received real-time data of power grid equipment; and the wireless sensor node and the gateway node are connected to a power supply module. The timely induction for internal risks of the power grid equipment and the judgment on the equipment running state of a circuit are realized, by utilizing the wireless sensor network system provided by the invention in the manner of data monitoring. The gateway node of the wireless sensor network system has high transmission speed and strong anti-jamming capability; the wireless sensor node and the gateway node can be used for efficiently acquiring and storing energy; and the long service lives of the wireless sensor node and the gateway node are realized.