24results about How to "Improve data storage efficiency" patented technology

The invention relates to the technical field of data storage management, in particular to a data storage method based on a large model. The method comprises the following steps: performing input class cluster fragmentation optimization on a target pre-training large model to obtain storage modulus fragmentation data; constructing an intelligent fragmentation storage strategy by using the storage modulus fragmentation data; obtaining target model training data; performing intelligent fragmentation storage on the target model training data by using an intelligent fragmentation storage strategy, and performing redundancy compression optimization to obtain dynamic redundancy storage index data; and training data storage space optimization is carried out according to the dynamic redundancy storage index data, and an optimized data storage strategy is obtained. According to the method, intelligent fragmentation storage and refined data redundancy compression are performed on the data, so that efficient and stable model training data access is realized, the problem of low data storage and access efficiency in a large model training process is solved, and the model training efficiency and reasoning real-time performance are remarkably improved.

The invention discloses a method for a multi-modal cloud fusion service platform, and relates to the technical field of cloud service platforms, and the method comprises the following steps: S1, connecting a data source of a user through an API interface, collecting data of different modals, and obtaining a user fusion service demand and an application scene; and S2, preprocessing the collected data, establishing a cloud storage database, providing a multi-modal cloud storage service, establishing a data index and the like. Different modal data are collected in multiple modes, data sources are expanded, data richness and diversity are improved, data quality is improved through data preprocessing, a reliable data basis is provided for follow-up analysis, data are conveniently and rapidly retrieved and queried in multiple data indexing modes, data storage and management efficiency is improved, and the method is suitable for large-scale popularization and application. And user portraits and clustering analysis are established, so that user demands can be better known, personalized multi-modal services are provided for different user groups, and user satisfaction is improved.

The invention relates to the technical field of integrated energy system control, in particular to an integrated energy system monitoring control method and an operation system, data is collected in real time, data preprocessing is carried out, a distributed computing architecture is utilized, data collection tasks are dispersed to a plurality of computing nodes, and a memory carries out classified storage on the data; the database server analyzes and processes the data, and establishes and optimizes an economic operation mode optimization model SOM and a safe operation mode optimization model EOM; and the optimized control scheme model parameters are fed back to a control end in real time, the scheme parameters are analyzed and calibrated and fed back to a processor, and the processor issues a detailed operation parameter command to the energy consumption equipment, so that the energy consumption equipment adjusts the operation parameters to achieve an optimized operation state. And the data processing capability, the communication reliability and the data storage and management efficiency of the system are improved, so that the efficient, stable and optimized operation of the comprehensive energy system is ensured.

The present application discloses a load balancing method and device based on an improved consistent hash ring, which is applied to a distributed cluster, wherein the distributed cluster includes at least two server nodes. The method includes: obtaining data to be stored and determining a hash value of the data to be stored; determining the first node that is closest to the hash value of the data to be stored in a clockwise direction on a created target hash ring as a candidate node, wherein the target hash ring is obtained by creating an initial hash ring based on the hash value corresponding to each server node, and creating a corresponding virtual node for each server node at a symmetric point on the initial hash ring; if the candidate node is determined to be any server node, the data to be stored is stored in the server node; if the candidate node is determined to be a virtual node, the data to be stored is stored in the server node corresponding to the virtual node.

The invention belongs to the technical field of memristors, and relates to a preparation method of a spider silk memristor for simulating nerve synapses, which specifically comprises the following steps: coating a conductive layer with a NaOH-spider silk protein solution to obtain a functional layer, and depositing an electrode layer on the functional layer to obtain the spider silk memristor for simulating nerve synapses. The preparation process of the NaOH-spider silk protein solution comprises the steps that degummed spider silk is dissolved in a NaOH aqueous solution, suction filtration and centrifugal treatment are directly carried out, the NaOH-spider silk protein solution is obtained, and the concentration of the NaOH aqueous solution is 50-200 mM. The memristor prepared by the method disclosed by the invention has a bionic nerve synapse characteristic, is stable in signal transmission, and can realize multiple stable erasing processes from a high resistance state to a low resistance state, so that the stability, durability and consistency of the memristor are remarkably improved.

Embodiments of the present application provide a kind of data processing method, device, equipment, storage medium and program product, wherein the method comprises: obtaining the equipment information reported by multiple metering instruments according to predefined time interval, and each equipment information is transformed, and the structured information flow corresponding to each metering instrument is obtained;According to the structured information flow corresponding to each metering instrument, perform time sequence verification operation;According to time sequence verification result and each structured information flow, generate time sequence data block, and send the time sequence data block to database, to make the database store the time sequence data in the time sequence data block;Wherein, the time sequence data block contains the ordered data set of the structured information with time sequence of each metering instrument.The embodiments of the present application can reduce the high cost caused by using high-end hardware materials, and improve data storage efficiency.

The invention relates to a data read-write method and device for a chip storage area, computer equipment, a storage medium and a computer program product. The method comprises the following steps: splitting a storage area of a chip into a plurality of sub-storage areas according to a storage area splitting strategy; according to the type of data which can be stored in each sub-storage area and the area residual capacity of each sub-storage area, performing data splitting on each piece of to-be-stored data to obtain each piece of sub-storage data of each piece of to-be-stored data; storing the sub-storage data of the to-be-stored data into the sub-storage areas respectively; in response to the data calling operation, determining a data type and a data identifier of target calling data needing to be called; according to the data type and the data identifier of the target calling data, calling each target sub-storage data belonging to the target calling data in each target sub-storage region; and splicing the target sub-storage data to obtain target calling data. By adopting the method, the data read-write efficiency improvement effect of the chip storage area can be improved.

The invention relates to a data storage method and device, computer equipment, a storage medium and a program product, and relates to the technical field of data storage. The method comprises the following steps: in response to a storage request of target data, a management node of the distributed database system determines a target available area from a plurality of available areas of the distributed database system; determining candidate data node groups of the target data according to the residual space rate of each data node group in the target available area; and determining a target data node group from the candidate data node groups, and storing the multiple copies of the target data to the target data node group. Wherein each available region comprises a plurality of data node packets. By adopting the method, the determination time of the data nodes can be shortened, and the storage efficiency of the distributed database system is improved.

The invention relates to the technical field of intelligent event processing, and provides an event dialogue collecting and processing method and system.The method comprises the steps that a corresponding cache instance is created according to a received dialogue request, and the cache instance is initialized; modifying a preset information extraction cue word template according to the cache instance, obtaining an information extraction cue word, and updating slot position information of the cache instance according to the information extraction cue word; when a picture is received in the dialogue, the cache instance is updated by analyzing and adding picture information, and when an instruction of deleting the picture is received in the dialogue, the picture is deleted by modifying the picture information in the cache instance; and modifying a preset content reply prompt word template according to the cache instance, obtaining a content reply prompt word, and generating dialogue reply content according to the content reply prompt word. Through accurate cache management, slot state control and picture content maintenance, the information acquisition and processing flow is optimized, the response speed and the data processing precision of the system are improved, and the intelligent level of user interaction is improved.

The invention discloses a logistics information intelligent integrated management platform and method and a storage medium, and relates to the technical field of logistics information management, and the platform comprises a data optimization demand analysis module, a data optimization label judgment module, a data compression execution module and a computing power enhancement execution module. According to the invention, targeted processing of the logistics data can be realized. Data which is in a service expansion period and has increased data volume but does not reach the computing power bottleneck can be compressed and optimized, so that the storage space is effectively released, the data management efficiency is improved, the influence of blind compression on key data is avoided, and the reasonability and effectiveness of data storage are improved. And when the data volume is increased sharply and processing is complex, computing power optimization can be triggered in time, it is ensured that the system efficiently processes large-scale complex data, efficient collaborative operation of all links of a logistics information chain is ensured in the data compression link, and the timeliness, accuracy and stability of logistics services are greatly improved.

The present invention discloses a graph-based BIM data storage management method, comprising constructing a data structure based on a multi-level graph, wherein the first-level graph is used to represent the overall architecture of different projects in the BIM model, the second-level graph is used to present the structural relationship between different partitions in each project, and the third-level and lower-level graphs are used to carefully depict the entities in the partitions and their mutual relationships; a unique identifier with a timestamp and a version number is assigned to each entity in the BIM data, and the identifier is associated with detailed attribute information including geometric information, material properties, construction technology, etc. and stored; a graph algorithm, such as a graph neural network algorithm based on deep learning, is used to deeply analyze and process the complex relationships in the BIM data to achieve efficient data query, update and prediction operations; the present invention can accurately represent the complex relationships and hierarchical structures in the BIM model by constructing a multi-level graph data structure, facilitates rapid positioning and operation of data, and significantly improves the efficiency of data storage and management.

This application discloses a test data backtracking method, apparatus, device, storage medium, and program product, relating to the field of software testing technology, aiming to solve the problem of difficulty in locating and investigating test data. The method includes: acquiring test data collected by a data acquisition agent server; the test data is data generated during the process of calling application programming interface (API) when electronic devices in the test environment run test cases; associating and storing the test data with the test case to which the test data belongs and / or the API called by the test data, and establishing multi-dimensional retrieval identifiers; responding to a data call request sent by a visualization platform, determining the target test data based on the retrieval parameters and retrieval identifiers requested in the data call request; and sending the target test data to the visualization platform so that the visualization platform can visually display the target test data.

The invention discloses a machine learning application-oriented multi-version unstructured data storage method, which specifically comprises the following steps of: (1) a distributed storage framework of unstructured multi-source data: processing and judging the multi-source data by utilizing a multi-version data storage strategy before the data is formally stored; the optimal storage strategy is selected based on the balance of the storage space and the retrieval time, and the data compression technology based on the neural network correspondingly compresses different types of data, so that the storage efficiency of a distributed database and the convenience of machine learning application in the data access and processing process are improved. (2) a multi-version data storage strategy: facing challenges of continuous generation of multi-source data and continuous change of storage versions; the method can be deployed in a distributed unstructured graph database, the storage process is independent and complete and has a global perspective, management and optimization of data storage can be realized, and the method is suitable for scenes of multi-type data sources and high-frequency data updating.

The present invention provides a data storage monitoring method and system for a hydropower fusion terminal, and relates to the technical field of agricultural irrigation equipment. After detecting a data storage instruction, the present invention performs security and integrity detection on the data content of the data to be stored to determine whether the data to be stored is normal, and then determines the transmission time and transmission mode according to the storage priority, splits the data to be stored into multiple data packets, and sends them to the hydropower system platform. The present invention performs a security and integrity detection before data storage and transmission, so that the hydropower system platform can directly store data, reduces the memory pressure of the hydropower system platform, and improves data storage efficiency. It solves the problem of low efficiency of storing agricultural irrigation data on the hydropower system platform, and improves the data storage efficiency of agricultural irrigation data.

The invention provides a data processing method and system of an electric energy meter and electronic equipment. The data processing method comprises the following steps: judging whether to-be-stored data is successfully written into a FLASH memory or not; if not, judging whether the number of rewriting times is greater than a preset number of rewriting times or not; if yes, the rewriting frequency is increased, and a target backup data block is determined based on a preset data block division rule; setting a backed-up mark on the read-only memory, storing to-be-backed-up data except the to-be-stored data in the target backup data block into the read-only memory, and erasing the target backup data block; when it is detected that the electric energy meter is in the re-power-on state after power failure, whether a backup mark exists in the read-only memory or not is recognized; and if the backed-up mark is identified, reading a data address corresponding to the to-be-backed-up data in the read-only memory, and writing the to-be-backed-up data into the target backup data block. The storage space of the electric energy meter can be saved, and the data storage efficiency and storage reliability of the electric energy meter during frequent power failure can be improved.

This invention discloses an intelligent computing center performance evaluation and optimization management system, belonging to the field of intelligent computing center management technology. The system includes a data acquisition module, a data preprocessing module, a performance evaluation module, an optimization decision-making module, an execution control module, and a data storage module. The data acquisition module uses IoT sensors and edge computing nodes to collect real-time operating data from various devices and transmits it encrypted. The data preprocessing module uses the Spark Streaming framework to clean and denoise the data. The performance evaluation module integrates a CNN-LSTM hybrid network and the Analytic Hierarchy Process (AHP) to generate a comprehensive performance score through a formula. The optimization decision-making module uses reinforcement learning and other algorithms, combined with a digital twin engine and energy consumption prediction formulas, to generate the optimal resource scheduling scheme. This system achieves comprehensive data acquisition, accurate performance evaluation, scientific optimization decision-making, and efficient execution control for intelligent computing centers, improving operating efficiency and reducing energy consumption, and has high practical value.

A method for dynamically positioning batches of materials in a stock bin belongs to the technical field of data processing, and adopts a conventional computer system as a data processing and storage platform, is equipped with a high-performance processor and a large-capacity storage device, accesses PLC production data through an OPC protocol, and collects related data of the stock bin in real time; using Python to develop a batch positioning algorithm; and a MongoDB database is used for storing the time sequence data. According to the method, the MongoDB database is used for storing the time sequence data, meanwhile, the character string is used for storing the time sequence data, all needed information is stored at a time, the data processing flow is simplified, the number of times of interaction with the database is reduced, and the data storage and reading efficiency is improved. By automatically calculating the feeding amount and the discharging amount in each period and updating the positions of the material batches in the stock bin in real time, the specific position of each batch in the stock bin is dynamically positioned in real time, manual intervention is reduced, and the accuracy and reliability of batch management are improved.

The invention provides a method, system and equipment medium for an Internet of Things platform to collect OPCDA protocol data, and belongs to the technical field of the Internet of Things. The method comprises the following steps: establishing communication connection between a client and an OPCDA server; the client sends a data request to the OPCDA server according to a service demand, and converts data acquired from the OPCDA server into data which can be identified by the Internet of Things platform; the client sends the converted data to a service end through a message queue; the service end stores the data received from the client into a relational database and a time sequence database; and the client requests the OPCDA server to cancel the connection. According to the invention, the rapid transmission and sharing of data are realized, the same operating system environment does not need to be maintained between the client and the OPCDA server, the dependence on the development environment is reduced, the development cost is obviously reduced, and the data interaction efficiency between the industrial system and the application of the Internet of Things is improved.

The application discloses a kind of plant specimen intelligent integrated management system, it is related to plant specimen management technical field, including management center, the management center includes information entry module, information processing module, information coordination module, information audit module and information traceability module;Through setting acquisition electronic tag and identification electronic tag, and the information item in standardization acquisition electronic tag and identification electronic tag, so as to directly enter the basic information and data information of entity specimen, and the basic information and data information of entity specimen are automatically summarized in corresponding information item, so as to reduce the operation time of manual input, improve information entry efficiency.

The invention provides a difference-based aircraft performance calculation mode for a domestic civil aircraft, and relates to the technical field of aviation, and the method comprises the following steps: S1, generating C919 and ARJ21 civil aircraft performance data as two-dimensional table data, and directly reading the performance data from a database according to query conditions, and S2, obtaining the performance data of the civil aircraft in the current state by using a difference calculation mode according to query list data. The domestic civil aircraft is based on a difference value aircraft performance calculation mode, domestic civil aircraft performance data is generated and imported into an MYSQL relational database, Java language is used for reading MYSQL domestic civil aircraft performance database data, difference calculation is conducted on aircraft performance data according to query conditions, and the performance data of the civil aircraft under the current condition is accurately obtained. Performance differences among different flight conditions and different aircrafts can be fully considered, the accuracy of performance data calculation is improved, the MYSQL relational database is adopted to store airplane performance data, and the data storage and query efficiency can be improved by utilizing the index and query optimization technology of the database.

The embodiment of the invention provides a data storage method and device, a storage medium and electronic equipment, and relates to the field of computers.The data storage method comprises the steps that a data storage request initiated by a first host is obtained, the first host is a host in a cluster, and all hosts in the cluster share a preset memory; the preset memory is jointly provided by each host, and the data storage request is used for requesting to store excessive data generated by the first host in the preset memory; determining at least one second host from other hosts based on the distribution priority of the excessive data and the storage priorities of the other hosts in the cluster; the excess data is stored in at least one second host. By adopting the scheme, the problem of relatively low data storage efficiency in related technologies is solved.

The invention relates to a data storage method and device, computer equipment, a readable storage medium and a product. The method comprises the steps of determining at least one data storage request; the data storage request carries to-be-stored data; controlling the request partitioning party to carry out striping processing on each data storage request to obtain at least two sub-requests; the data access system comprises a request partitioning party; selecting a target processing party corresponding to each sub-request from at least two request processing parties in the data access system, and controlling the request segmentation party to output each sub-request to the corresponding target processing party; and controlling the target processing party to respond to the corresponding sub-request. By adopting the method, the data storage performance of the cloud hard disk can be improved.

The present application provides a method and device for recovering and allocating index data in a hash table, the method comprising: allocating a RAM target address space for a target hash table in the current RAM; allocating a DDR target address space for a target hash table in the DDR; allocating each index data to be recovered in the target hash table to the DDR target address space; reading a preset number of the index data from the DDR target address space and writing them to the RAM target address space; based on the index recovery instruction received from the user input, reading the first RAM address pointer in the index parameter table corresponding to the user; based on the first RAM address pointer in the index parameter table, writing the target index data pre-read from the RAM target address space to the RAM target address space; and adding 1 to the value of the first RAM address pointer to obtain a second RAM address pointer. The present application can effectively improve the efficiency of DPU data storage and reduce the data storage pressure of DPU.