30results about How to "Quickly respond to business needs" patented technology

The invention discloses a cloud computing resource internet of things supervision and service platform which comprises a supervision and service platform body and a client. The service platform body comprises a database, a data acquisition and interface layer, a technical support layer, an analytical model layer and an application service layer, the application service layer is connected with the client, and the database is connected with a data control system and a dispatching and monitoring system. The cloud computing resource internet of things supervision and service platform is constructed by the aid of the database, the data acquisition and interface layer, the technical support layer and the analytical model layer according to actual requirements of supervision and service of IT (information technology) resources, comprises an IT asset and configuration management module, an IT asset integration monitoring module, an IT operation and maintenance guarantee module, a service guarantee and measurement module, a service guarantee reporting module and the like, can rapidly respond to business requirements, and aims to improve operation and maintenance guarantee efficiency and the capacity of preventing and solving failures, so that reliability of information systems is improved.

The invention discloses a service data processing system and method based on a data middle platform. The system comprises the data middle platform and a data acquisition device, The data acquisition device is used for acquiring data source information of at least one service platform; the data middle platform analyzes and processes the acquired data source information to generate a data source inthe same service scene; and the data sources under the same service scene are taken as service data for the foreground to respond to the service requirements of the foreground. According to the scheme, logic packaging is carried out on multi-source mass data to form the data middle platform, and standardization of service data is achieved; by use of the data middle platform technology, data islands are broken, data structures are integrated, data exits are unified, a data closed loop is formed, various data such as client acquisition, medium channel management, marketing links, operation conditions and financial management are connected in series, and the situation that data drives business development can be formed.

The invention discloses a relational database query method, device and equipment and a storage medium. The method comprises the steps that when it is detected that connection between a current projectand a database is successful, a database management system function is called to obtain an original data result set of the database; Reading metadata of the database from an original data result set,and generating a metadata model based on the metadata and through the database management system function; Creating and constructing a query function based on the metadata model; the structure of thedatabase is changed; a programmer does not need to modify a source code related to the database query statement in the current project; and the database can be queried by directly calling the construction query function, so that the workload of a programmer in development and testing is effectively reduced, meanwhile, the service requirement can be quickly responded, and the experience degree ofa user on project software is improved.

The invention discloses a data privacy calculation method and system based on a block chain. The data privacy calculation method comprises the following steps: after any node on the block chain receives a data privacy calculation request sent by a data demander, issuing a service node voting request in the block chain, wherein all the nodes in the block chain determine a target service node from all the nodes of the block chain by using a preset consensus algorithm according to the service node voting request; and enabling the target service node to execute the data privacy calculation request. According to the invention, the security and credibility of data of the coordinator can be improved.

The invention relates to a banking industry-oriented full-stack financial knowledge graph platform, which comprises a graph construction layer configured to perform source data management, logic graph ontology creation, graph production, graph treatment and task scheduling; the map warehouse management layer is configured to store maps of different fields for specific business scenes; the service application layer is configured to perform map visual search, map data mining, map query and map model application; and the application interface layer is configured to provide financial knowledge graph service access capability for the platform. Compared with the prior art, the method has the advantages that key graph management links of knowledge acquisition, knowledge representation, knowledge storage, knowledge fusion, knowledge modeling, knowledge calculation and knowledge application are realized, the whole process from knowledge raw materials to intelligent data conversion is supported, full-stack graph production and application service capability is provided, and graph construction and production efficiency is improved.

The invention discloses a single-source multi-node data synchronization method and system, and relates to the field of data synchronization. The method comprises the following steps: establishing a change data table through a trigger, inserting a plurality of change data into the change data table, respectively reading the plurality of change data through a plurality of nodes, and selecting to-be-synchronized data in the change data for synchronization. According to the method, multiple change data in the change data table are read through multiple nodes; and to-be-synchronized data in the change data are selected for synchronization, so that trigger data of only one data source is generated. Therefore, the data can be synchronized to any node, the timeliness of data synchronization is considered, and junk data generated by a database and the pressure of the database are reduced.

The invention discloses a method and a system for registering a service, and a method and a system for invoking a service. Among them, a method for registering a service, comprising the following steps: the server sends a registration request to the server agent; the server agent parses the registration request, and records the service information obtained by parsing in the first service list, and The service information is sent to the client agent; the client agent updates a second service list according to the service information for the client to access, wherein the second service list is the same as the first service list. Compared with the prior art, the present invention can realize data transmission between the server and the client even if they are not in the same local area network by setting the server agent and the client agent.

The invention discloses an implementation method for permanent storage virtual machine restoration based on an openstack cloud management platform. The method comprises the following steps: step 1, enabling a client to initiate a request for creating an automatic restoration virtual machine; 2, performing parameter legality check on the automatic virtual machine creation request; 3, performing operation authority check on the automatic virtual machine creation request; 4, creating an automatic virtual machine restoration operation, and filtering and selecting an optimal virtual machine operation node; 5, performing virtual machine starting parameter preparation, and starting the virtual machine in an automatic restoration mode; 6, obtaining the current creation state of the automatic restoration virtual machine; and 7, obtaining the current operation mode of the virtual machine, and operating the virtual machine at any time for restoration. According to the implementation method for permanent storage virtual machine restoration based on the openstack cloud management platform, a method for automatically restoring the virtual machine to be in a state before use after the virtual machine is restarted is provided, and the state of the virtual machine is restored quickly and stably without any snapshot data restoration and other operations.

The embodiment of the invention provides a pooling method and device for retail risk exposure, computer equipment and a medium, and relates to the field of automatic programming. The method comprises the steps of obtaining a sample used for constructing a model in a feature wide table corresponding to retail risk exposure; performing high-level subdivision on the sample in response to user configuration; and performing layer-by-layer subdivision on samples in the sample set obtained by high-level subdivision according to the pooling risk factors, and generating a retail risk exposure pooling model based on a high-level subdivision result and a layer-by-layer subdivision result. According to the embodiment of the invention, standardization and automation of construction of the retail risk exposure pooling model are realized, and the development time of the retail risk exposure pooling model is greatly shortened; in the aspect of model iteration, iteration can be performed in response to user configuration so as to quickly respond to business requirements, and the model iteration efficiency is improved; and the modeling process risk is controlled to a certain extent, and errors caused by manual operation are reduced.

The invention provides a business data concurrent processing method, a device thereof and a system, belongs to the technical field of cloud computing, and can be applied to the financial field or other fields. The business data concurrent processing method comprises the steps of obtaining business input parameters, and determining rules corresponding to the input parameters and element information of elements corresponding to the rules; sending the element information of each element to a corresponding cluster client, so that each cluster client obtains an element value of each element information in parallel; and concurrently executing the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result. The system expansibility, the operation stability and the service data processing efficiency can be improved, and related service requirements can be quickly responded.

The invention discloses a label updating method and device, a computer readable storage medium and electronic equipment. The method relates to the field of artificial intelligence, and comprises the steps that a label corresponding to each object in a to-be-screened set is acquired, a plurality of labels are obtained, the to-be-screened set is composed of a plurality of objects, and the plurality of labels represent object features of each object in the to-be-screened set; determining a plurality of target tags from the plurality of tags, and determining screening conditions corresponding to the plurality of target tags; combining the screening condition corresponding to each target label in the plurality of target labels to generate a combined label; and updating the plurality of tags corresponding to the to-be-screened set based on the combined tag to obtain an updated tag set. The technical problem that in the prior art, the label updating efficiency is low due to the fact that the label is obtained by processing the source data is solved.

The invention relates to the field of cloud computing, in particular to an elastic telescopic group configuration method. According to the elastic scaling group configuration method, an expected number of virtual machines are distributed to the cloud platform initially, and the distributed virtual machines are not the maximum number of virtual machines required by the elastic scaling group at the moment; and then in the running process of the cloud platform, when it is judged that the load state of the cloud platform does not reach a preset degree, namely, when the load state is better, the virtual machine is started and created to build the virtual machine, and resources such as a CPU and a memory of a physical host in a working state do not need to be excessively occupied at the moment. When the elastic scaling group needs to be expanded, the elastic scaling group can be directly added without creating a new virtual machine, so that the time consumed for creating the virtual machine can be shortened when the virtual machine is expanded, the speed of expanding the virtual machine is greatly improved, and the elastic scaling group can quickly respond to business requirements.

The invention discloses a method for transmitting short messages, which includes: the extending entity of the short message sends a short message to the control center which makes a judgment about the message whether it is to be group-sending or not. If it is, the short message is split into short messages with a single purpose of destination. The control center sends the split messages to the receiver terminals. This invention also discloses a system for sending short messages including: expanding the short message entity for transmitting short messages to the dispatch center, a short message dispatch center for judging if said one is of group messages, if so, it is split into one containing single destination address to be sent to the terminal user. This invention also discloses a shortmessage dispatch center.

A method and device for automatically arranging fans based on mesoscale data, the method comprising: first screening an input wind field area by using a wind speed limit value according to input mesoscale wind atlas data to obtain a first wind field area ; According to the input terrain data, use the gradient limit to screen the first wind farm area again to obtain the second wind farm area; use the tabu search method with the target number of fans and the second wind farm area as input to determine the target The wind turbine arrangement with the optimal function, wherein the objective function is the sum of the annual power generation for the wind turbine points.