308 results about "Dynamic storage" patented technology

The invention discloses a cargo warehouse-in and warehouse-out management method and management system, and relates to the technical field of information management. Through dynamic storage position optimization, the warehouse-in and warehouse-out frequency, the associated sales relationship and the storage demand characteristics of cargos are combined with a warehouse three-dimensional space model; and generating a cargo storage location allocation scheme by using a multi-objective optimization algorithm. According to the scheme, the picking time of high-frequency warehouse-in and warehouse-out commodities is remarkably shortened, the average time consumption of single-time commodity picking is reduced, meanwhile, the combined picking error rate of associated commodities is reduced, the problem that in the prior art, storage positions are disjointed with warehouse-in and warehouse-out requirements is solved, through predictive process scheduling, cross congestion of operation channels is effectively avoided, and the working efficiency is improved. Therefore, smooth operation of the in-out warehouse process is realized, the occurrence frequency of congestion events of the in-out warehouse channel is reduced, the delay time is shortened, and the problem of congestion of the in-out warehouse process in the prior art is solved.

The invention relates to an ERP non-core service migration method based on K8s dynamic resource scheduling, and belongs to the technical field of cloud computing containerization and ERP system optimization. The method comprises the following steps: identifying a non-core module based on business criticality, and generating a migration list; an internal interface is transformed into a standard API gateway route, and strong dependency communication is asynchronously decoupled through a message queue. Historical resource load data is collected, a periodic rule is extracted by using a time sequence decomposition model, a reference value is set, and a K8s scheduling parameter is generated. Adopting multi-stage construction to separate compilation and operation environments, and generating a lightweight mirror image; and implementing security reinforcement, and dynamically updating the health examination probe and configuration. Selecting a controller according to stateless and persistent requirements; the locality of NUMA domain resources is optimized through topology awareness scheduling; dynamic storage binds a persistent volume according to QoS; the network policy implements container-level traffic isolation. And dynamically adjusting the resource quota and the number of copies. The efficient and safe migration of the ERP non-core business in the K8s environment is realized.

The invention relates to the technical field of smart community data management, in particular to a smart community metadata interaction method and system based on an edge computing framework, and the method comprises the steps: carrying out the dynamic storage of multi-dimensional data through a hierarchical rolling cache; generating a uniform resource vector through sequential progressive mapping; community semantic tags are added for the uniform resource vectors through extensible tag slots, connection is established according to association rules, and a resource semantic graph oriented to community services is constructed; receiving a resident task request, constructing a multi-factor weighted scoring engine based on the resource semantic graph, and generating a task data packet with a priority label; a two-channel hybrid scheduling network is constructed, a first channel outputs resource availability and node association degree, and a second channel outputs time sequence characteristics and load prediction parameters; and fusing dual-channel output to obtain task-node correlation and generate an optimal matching strategy. According to the method, task collaboration and resource adaptive management are realized through semantic resource modeling and hybrid scheduling.

The invention relates to the technical field of enterprise office collaboration, and discloses an enterprise series intelligent office collaboration data processing system based on edge computing. The system comprises a collaborative data acquisition module, a collaborative feature analysis module, an edge task scheduling module and a dynamic storage optimization module. The collaborative data acquisition module is deployed at a local edge node of an enterprise, captures a collaborative operation behavior flow of the multi-source office terminal in real time, and extracts space-time distribution features to generate an original collaborative feature vector; the collaborative feature analysis module analyzes the coupling strength of related data through a multi-dimensional correlation analysis engine, quantifies the frequency fluctuation amplitude of a communication session, and fuses to generate a collaborative efficiency quantized value; the edge task scheduling module dynamically divides task load levels based on the value, and matches execution priorities to generate a distributed calculation task allocation strategy; and the dynamic storage optimization module responds to the strategy, monitors the throughput delay of the storage nodes, reconstructs a high-frequency access data storage index, and generates a cross-node storage topology configuration.

The invention discloses a cloud big data storage management method, and the method comprises the steps: carrying out the classification of multi-element access habit feature vectors of all terminal nodes through a preset classification model based on the multi-element access habit feature vectors of all terminal nodes, and obtaining a plurality of terminal node groups; based on all the terminal node groups, a first node network and a second node network are constructed, the first node network is used for carrying out distributed storage on the data, and the second node network is used for carrying out distributed backup on the data; monitoring and obtaining target data and a source tracing point thereof in real time, and generating an association processing instruction of the target data according to a preset differentiated source tracing processing decision, the association processing instruction including storage, backup and forwarding; and periodically executing the steps according to a preset time interval. Therefore, based on the dynamic node network, dynamic storage and backup of data are realized, the change of access habits of terminal nodes is adapted, failure storage of nodes in an off-line state is reduced, and the reliability of storage resources is improved.

The invention discloses a homomorphic encryption-based quantum security key management method and system, and belongs to the technical field of data processing, and the method comprises the following steps: obtaining and evaluating equipment encryption feature parameters and communication environment parameters, and obtaining a quantum encryption demand analysis result; generating a quantum security key and a dynamic storage index; obtaining a performance indication parameter of the quantum security key, performing evaluation to obtain a quantum security key transmission performance demand index, synchronously obtaining a transmission quality parameter of each quantum security key transmission channel, and performing analysis to obtain a key transmission channel corresponding to the quantum security key; based on the dynamic storage index and a key transmission channel corresponding to the quantum security key, the quantum security key is stored to a central processing unit, and a quantum security key hiding risk index is evaluated, so that whether quantum security key updating management needs to be carried out or not is judged; the problem that key generation and storage strategies cannot be dynamically adjusted according to specific encryption requirements in the prior art is solved.

The invention relates to the technical field of data storage, and discloses an intelligent hierarchical storage method and system for cold and hot data of a solid state disk, and the method comprises the steps: collecting spatial position change data and vibration state data, and carrying out the preprocessing to obtain a multi-dimensional feature data set; performing quantification processing on the influence degree of the spatial position change data and the vibration state data to obtain an interference weight value; constructing a joint feature matrix based on the interference weight value and the historical access record, and predicting hotspot data distribution; if the matching degree of the hotspot data distribution and the current storage layout is lower than a preset matching degree threshold value, migrating the high-frequency access data to a low-delay area to obtain an optimized storage layout; when the access response time is larger than a preset time threshold value, log data are generated, and delay load features are extracted; and carrying out secondary adjustment on the optimized storage layout to obtain a final dynamic storage scheme. According to the method, dynamic optimization of the storage performance of the solid state disk can be realized, and delay loss caused by cold and hot data mismatching is reduced.

The invention provides a dynamic storage intelligent sorting method, system and equipment based on production takt, and a medium, which can improve the adaptability of the sorting system to the production takt, optimize the inventory circulation efficiency, reduce the risk of production interruption caused by material mismatching or supply delay, and improve the production efficiency. The method comprises the following steps: collecting real-time parameters of production takt of each key station on a production line, and obtaining demand information of target materials to be sorted; based on the real-time parameters of the production takt and the demand information, the production takt prediction parameters and the material demand prediction quantity of each key station in a future period of time are predicted, and in combination with the current inventory state, the equipment availability and the preset optimization parameters, a dynamic storage location adjustment plan and an optimal sorting task sequence currently suitable for a production line are generated and are used as the basis; and the flexible dispatching mechanism is dispatched to dynamically adjust the physical positions of the corresponding materials, then the sorting mechanism is called to sort out the target materials with the specified number from the dynamically adjusted storage locations, and then the target materials are sorted to the corresponding target stations.

The invention provides an intelligent refrigerator article storage management method and system. The method comprises the steps that accurate basic data is provided for dynamic storage optimization and healthy diet recommendation; the partition and environmental parameters are dynamically adjusted according to the storage requirements of the food materials, and the preservation time is prolonged; the fresh-keeping state and the storage environment of the food materials are evaluated in real time, and the partition optimization effect is ensured; recording food material taking behaviors of the user, and generating a healthy intake model; and generating personalized diet recommendation and reminding in combination with the health demand and the storage state of the user. According to the intelligent refrigerator article storage management method and system, the food material storage efficiency is optimized through the intelligent technology, the food material utilization rate is increased, and meanwhile the personalized healthy diet requirement of a user is met.

The invention relates to the technical field of storage automation, and particularly discloses an electric power storage dynamic storage location distribution method and system fusing multi-dimensional factors, and the method comprises the following steps: constructing an electric power storage digital twin environment based on edge calculation, collecting multi-source heterogeneous data in real time through an OPC-UA protocol, and building a three-dimensional data association model; and based on the three-dimensional data association model, extracting a 28-dimensional state vector, and constructing a reinforcement learning state space. According to the power storage dynamic storage location allocation method and system fusing the multi-dimensional factors, a real-time mapping storage virtual environment is constructed through edge calculation and a digital twinning technology, and intelligent upgrading of power storage management is realized in combination with reinforcement learning and a cross-system linkage rule; according to the scheme, storage location distribution can be dynamically optimized according to multi-dimensional parameters such as the remaining service life and the maintenance cycle of the equipment, the storage space utilization rate and the equipment scheduling efficiency are remarkably improved, and the intelligent and automatic level of electric power storage is comprehensively improved.

The invention provides a digital enterprise management data storage method and system based on cloud computing, and the method comprises the steps: obtaining a real-time management data set in an enterprise data flow, generating a virtualized storage node, determining a target encrypted fragment index matched with the virtualized storage node according to a preset storage path optimization model, and storing the target encrypted fragment index into a database; based on a dynamic storage path corresponding to the target encrypted fragment index, segmenting the structured data block and the unstructured data block into encrypted data units distributed across regions, and mapping the encrypted data units to corresponding cloud storage partitions; dynamically distributing storage resources of the cloud storage partitions through a load balancing algorithm, and adjusting priority weights of dynamic storage paths according to real-time flow characteristics; and when an access request of the encrypted data unit is detected, redistributing the concurrent connection number of the cloud storage partitions. According to the method, the collaborative optimization problem of resource allocation and safety efficiency can be solved.

The invention provides a time sequence data storage method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining time sequence data and metadata information of the time sequence data, the metadata information comprising a first point location identifier, a data source and a data type corresponding to the time sequence data; according to the data source and the data type, determining a storage strategy of the time series data, including a target storage period and a target storage position; according to the storage strategy and the first point position identification, a target storage instance corresponding to the time sequence data is matched from a storage instance set, all storage instances in the storage instance set are combined and constructed according to different storage strategies and the point position identification, and all the storage instances are parallel storage instances; and storing the time sequence data to a time sequence database through the target storage instance. By determining a dynamic storage strategy driven by metadata and a parallel storage instance, the problem of performance bottleneck during high-concurrency writing of massive time series data is solved, and the real-time performance and reliability of time series data storage are ensured.

The invention discloses a dynamic storage system, a dynamic storage method, electronic equipment and a storage medium, and relates to the technical field of data storage. The dynamic storage system comprises an environment perception module, a user behavior prediction module and a storage strategy generation module. The environment sensing module is used for acquiring operation environment parameters of the solid state disk and generating an environment survival weight based on the operation environment parameters; the user behavior prediction module is used for acquiring historical access data of the solid state disk and generating a user behavior weight based on the historical access data; the storage strategy generation module is used for determining a dynamic storage strategy of the solid state disk according to the environment survival weight and the user behavior weight, the technical problem that a current solid state disk lacks active adaptive capacity in the aspect of data storage is solved, and the dynamic storage strategy of the solid state disk is obtained according to environment perception and user behavior prediction. The technical effects of dynamically adjusting the storage strategy of the solid state disk, improving the active adaptive capacity of the solid state disk, reducing the bit error rate and improving the reliability of data storage are achieved.

The invention discloses a warehousing system for waste automobile power batteries, and relates to the technical field of warehousing management, and the system comprises a safety evaluation module which analyzes a feature data set through an artificial intelligence algorithm, and generates safety risk level labels and recommended storage environment parameters of the power batteries; the configuration scheme generation module automatically classifies and dispatches the safety risk level labels of the power batteries to the matched storage areas, configures a temperature and humidity control device according to the recommended storage environment parameters, and generates a dynamic storage configuration scheme; and the storage data recording module is used for carrying out structured integration on the state monitoring data set, the power battery tracking data, the safety risk level label and the dynamic storage configuration scheme by utilizing a multi-source data fusion algorithm to generate a storage data record. According to the invention, accurate classification and prediction are realized, so that the storage condition of the battery is dynamically adjusted without manual intervention.

The invention relates to the technical field of cloud storage, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a hierarchical storage method, device and equipment for data files and a medium, and the method comprises the following steps: acquiring the data files in a storage unit, and extracting data characteristic parameters in the data files; performing multi-dimensional quantitative analysis on the data feature parameters to obtain a dimensional feature analysis value; identifying a dynamic weight of the data feature parameter, and performing weighted calculation on the data feature parameter according to the dimension feature analysis value and the dynamic weight to obtain a dynamic storage analysis value; identifying a data storage type label according to the dynamic storage analysis value; matching the data storage type label with strategies in a storage strategy library to obtain a target storage strategy; determining a storage hierarchy according to the target storage strategy; a storage address of the data file in the storage hierarchy is identified and the data file is stored in the storage address. The accuracy of hierarchical storage of the data files can be improved.

The invention relates to the technical field of frequency control, in particular to a frequency regulation and control method and system of an ultrasonic cleaning machine based on cleaned objects. The method comprises the following steps: acquiring an image of a cleaned article and article material data; determining the pollutant type of the cleaned article based on the article material data and the cleaned article image, and integrating to generate the feature data of the cleaned article; constructing an ultrasonic frequency database; importing the characteristic data of the cleaned article into the characteristic data of the cleaned article to perform optimal ultrasonic frequency matching, and performing dynamic storage frequency adjustment on an ultrasonic frequency database according to a matching result to generate article cleaning ultrasonic matching data; setting the initial frequency of the ultrasonic cleaning machine based on the article cleaning ultrasonic matching data, and monitoring the cleaning process of the ultrasonic washing machine according to the initial frequency. Through precise matching, dynamic adjustment and self-adaptive optimization of the ultrasonic frequency, the intelligence and accuracy of the ultrasonic cleaning process are improved.

The invention relates to the technical field of knowledge maps, in particular to an intelligent networked automobile data processing system based on data elements and knowledge maps, and the system comprises a data element definition module which analyzes original intelligent networked automobile data elements, distinguishes the original intelligent networked automobile data elements into a vehicle static parameter set and a vehicle dynamic parameter set, and forms a structured map blueprint. According to the method, element analysis is carried out on the intelligent network connection automobile data, and the intelligent network connection automobile data is divided into the static parameter set and the dynamic parameter set, so that the data has hierarchical structural characteristics, and the controllability and definition of subsequent data processing are improved. And in combination with differentiated structure construction of the static storage layer and the dynamic storage layer, a hierarchical data configuration model with clear logic is formed, and the data scheduling efficiency and the system load stability are improved. A geographic grid coding mode is introduced, space division is carried out on entity data with position attributes, spatial dimension information is made to have high-density indexability, and positioning and regionalization operation can be achieved easily.

Dynamic storage location allocation and strategy adjustment system (100) for SAP Extended Warehouse Management (EWM) environments, comprising: a) a real-time warehouse data aggregation module configured to collect SKU attributes, inventory levels and bin location availability from SAP EWM; (b) a dynamic bin allocation engine that applies artificial intelligence algorithms to allocate optimal bin locations based on SKU characteristics, space utilization and operational parameters; c) an adaptive strategy adjustment module that dynamically modifies storage and retrieval strategies in response to real-time storage conditions; (d) a pattern recognition and forecasting module configured to analyze historical trends and predict inventory and demand fluctuations; (e) a warehouse resource optimisation module that aligns decisions on the allocation of storage space with the availability of labour and equipment; f) an SAP EWM integration module that communicates with SAP EWM via APIs or BAdIs to implement changes in real time; and g) a review and feedback learning module that tracks system decisions and results to continuously improve allocation and strategy logic.

The invention relates to the technical field of warehouse logistics, and discloses a warehouse scheduling method based on WMS and AGV cooperation. The method comprises the following steps: constructing a dynamic storage location data center, and integrating storage location occupation states, material turnover rates and other parameters; generating a dynamic storage location allocation scheme by using a multi-factor decision algorithm; according to the real-time warehouse-in and warehouse-out instruction, an AGV carrying task chain is generated according to a task decomposition rule; constructing a multi-AGV cooperative path planning network by using the space-time map; inputting the storage location allocation scheme and the path planning network into the coupling scheduling model to generate an AGV cluster scheduling instruction set; and an AGV driving track is adjusted through an anti-collision optimization algorithm, and a final scheduling strategy is output. According to the invention, intelligentization and high efficiency of storage scheduling are realized, the storage space utilization rate, the operation efficiency and the safety are improved, the operation cost is reduced, and the method is suitable for various storage logistics scenes.

The invention relates to an information compiling technical method based on a Julia fractal set, and the method comprises the following steps: S1, information coding: converting input information into a binary ASCII code, mapping the binary ASCII code into a complex number, and generating a Julia set image with a specific fractal feature; s2, obtaining a fractal dimension D: obtaining the fractal dimension D of the fractal image through a box counting method, and taking the fractal dimension D as a feature value of the information; s3, information hiding and storage: storing the fractal image feature data and the fractal dimension D in a database to realize dynamic storage of the information; and S4, information decoding and error correction: in the decoding process, obtaining the fractal dimension D of the fractal image, reversely deriving original information by taking the fractal dimension D as an index, and realizing error correction by utilizing fractal self-similarity. According to the method, the concealment of information, the efficient compression of data and the anti-interference capability can be realized by using the self-similarity and the high complexity of the fractal image.

The invention discloses a data real-time analysis and fault early warning method and system based on a digital electric port box transformer substation, and belongs to the technical field of power equipment monitoring and control systems. The method comprises the following steps: acquiring environmental parameters of each component of the box transformer substation in real time through a monitoring network, and performing data smooth denoising to obtain a parameter sequence; constructing a dynamic storage framework based on the sequence in combination with space-time attributes; extracting historical records of the target component to perform multi-dimensional sorting and change rate calculation, and identifying potential anomalies; when the change rate exceeds the limit and the distribution boundary breaks through, generating an alarm sequence and determining a preliminary abnormal mark; comparing the mark with the historical record, fusing the influence weight analysis verification accuracy, and obtaining a final early warning grading result; and parameter summary information is pushed to a control system according to a grading result, response feedback is obtained, and closed-loop control of the operation state is formed. According to the invention, the problem of control lag caused by data noise and delay is solved, and the timeliness, reliability and automation level of box transformer substation control are improved.

A system (100) for a supply chain ecosystem comprising computing devices (160, 260, 460) having a processor (264) and memory storing computer-executable instructions that, when executed by the processor (264), cause the system (100) to obtain extrinsic data (1102) for processing. During a first processing, the extrinsic data (1102) is processed using a first neural network model (266, 466) trained with extrinsic training data to generate a first set of processed data (1104). Intrinsic data (1202) is obtained for processing. During a second processing, the intrinsic data (1202) and the first set of processed data (1104) are processed using a second neural network model (266, 466) trained with intrinsic training data and processed extrinsic training data to generate a second set of processed data (1204). Based on the second set of processed data (1204n), one or more unplanned and unanticipated events to a supply chain disruption are determined.

The invention discloses a fire-fighting equipment availability monitoring and intelligent three-dimensional warehouse storage management system, and relates to the technical field of warehouse management, and the system comprises an intelligent three-dimensional warehouse storage module which is used for storing fire-fighting equipment and carrying out the access management of the fire-fighting equipment based on an automatic access system and a robot scheduling system. The intelligent three-dimensional warehouse storage module comprises a fire-fighting equipment pre-distribution mechanism based on dynamic storage optimization, and the fire-fighting equipment pre-distribution mechanism based on dynamic storage optimization is combined with fire risk analysis, historical fire-fighting equipment use data and fire-fighting equipment service life prediction data to dynamically adjust the storage position of fire-fighting equipment. The fire-fighting equipment availability monitoring module is designed, so that the functions of real-time monitoring and fault prediction of the fire-fighting equipment are realized, the problem of equipment failure caused by long-time non-use or equipment aging is solved, the availability and reliability of the equipment are improved, and fire emergency work is guaranteed.

The invention belongs to the field of computer system structures and artificial intelligence accelerators, and discloses a software and hardware collaborative heterogeneous storage computing accelerator oriented to full-chip DLRM reasoning. A control domain composed of a static random access memory and an embedded dynamic random access memory, an on-chip storage domain, an in-memory computing domain and an on-chip computing domain are integrated in the same chip, an embedded table is compressed by introducing a hierarchical clustering quantization frame, and a dynamic storage management strategy of access frequency perception is combined. The embedded access path is shortened, and the bandwidth requirement is reduced. According to the method, the reasoning process of the whole set of DLRM can be independently completed, and the memory access overhead in a traditional terminal SoC is remarkably reduced by reducing cross-domain data migration between the calculation unit and the storage unit, so that the model reasoning performance and energy efficiency are improved.

Dynamic memory operations are described herein. According to the techniques, a system includes a stacked memory and one or more memory monitors configured to monitor a condition of the stacked memory. The system manager is configured to receive a monitored condition of the stacked memory from the one or more memory monitors and dynamically adjust operation of the stacked memory based on the monitored condition. In one or more embodiments, a system includes a memory and at least one register configured to store a ranking of each of a plurality of portions of the memory. Each respective ranking is determined based on an associated retention time of a respective portion in the memory. The memory controller is configured to dynamically refresh portions in the memory at different times based on a ranking of each of a plurality of portions of the memory stored in the at least one register.

The invention provides a storage device, an electronic device, a data storage method and a storage medium, and relates to the technical field of data processing, the storage device comprises a CXL interface module, a dynamic memory module, a flash memory module and a flash memory controller module; wherein the dynamic memory module comprises a plurality of device side periodic regions, the flash memory module comprises a plurality of data placement units, and the device side periodic regions are in one-to-one correspondence with the data placement units; the CXL interface module is used for receiving host data from the host side periodic region and temporarily storing the host data in the equipment side periodic region corresponding to the host side periodic region in the dynamic memory module; the dynamic memory module is used for packaging the host data in the equipment side periodic region after preset time; and the flash memory controller module is used for storing the encapsulated host data into a data placement unit corresponding to the equipment side periodic region in the flash memory module. The storage device effectively improves the write amplification phenomenon.

The invention relates to the technical field of data processing, in particular to an intelligent data storage and knowledge base integrated management system enabling an AI large model. The system comprises a data hierarchical storage module, a hybrid index construction module, an integrated knowledge base establishment module and an integrated knowledge base index module. Firstly, a data value score is calculated based on a multi-dimensional evaluation index, and a dynamic storage grading mechanism is established; secondly, a three-layer mixed index structure is adopted to index different types of hierarchical data, storage positions are adjusted, and a multi-source heterogeneous data storage layer is obtained; fusing the entity relationship to generate a triple, constructing a dynamic knowledge graph, and introducing an incremental updating mechanism to update in real time to obtain an integrated knowledge base; and finally, inputting a natural language, performing semantic analysis, obtaining a multi-modal index result by adopting a mixed index, and establishing an integrated knowledge base self-diagnosis mechanism. According to the method, the multi-source heterogeneous data is analyzed and processed, so that the purposes of data storage and knowledge base integrated management are achieved.

The invention provides a memory management method and a memory controller. The memory management method is applied to the storage device provided with a memory module and a buffer memory. The method comprises the steps of determining a necessary function and a high-frequency call function as a first type function by analyzing a call relationship of functions in a firmware program, and pre-loading the first type function into a resident storage area of a buffer memory; dividing the rest of the second type functions into a plurality of storage libraries according to the function calling relationship, and storing the rest of the second type functions in a storage module; and when the specific function needs to be executed, dynamically loading the storage library containing the target function into the dynamic storage area of the buffer memory. According to the method, through weight calculation and an intelligent allocation strategy, the number of times of switching of a storage library (Bank) can be reduced, so that the resource utilization rate of a memory is improved, the overall performance of a system is improved, automatic management of firmware codes is achieved, and the complexity and error risk of manual adjustment are reduced.

The invention discloses an intelligent storage automatic control optimization method and system based on dynamic environment perception, and relates to the technical field of intelligent storage control. According to the method, a specific scene type of a specified warehouse is firstly obtained, a corresponding dynamic perception allocation scheme is determined through scene matching, and then a collaborative operation association object is determined, so that accurate adaptation of dynamic environment perception and a warehouse scene is realized; then, collecting dynamic environment sensing data of a storage area where a collaborative operation association object is located, and after collaborative association processing is carried out, generating a structured fusion data set adapted to different time sequence scenes; dynamic storage parameter calibration is carried out, an initial control strategy is generated, and effectiveness evaluation is completed; whether the path planning scheme and the operation execution sequence are dynamically adjusted or not is decided according to the evaluation result, dynamic adaptation and accurate regulation and control of intelligent storage automatic control are achieved, and the adaptability of storage control, the smoothness of process operation and the stability of operation execution in a complex dynamic scene are effectively improved.

The invention relates to the technical field of electronic design automation, in particular to a function coverage rate data compression and storage method, system and device and a storage medium. Collecting the coverage rate of each coverage point or cross coverage and the hit times of each bin subordinate to the coverage point or the cross coverage; acquiring a coverage rate grade and a corresponding data structure; dynamically selecting a target data structure according to the target coverage rate grade of the coverage rate of the target coverage point or the cross coverage; operating a corresponding target data structure through a dynamic storage selector according to the target data structure, wherein the target data structure comprises a flag bit of the current data structure and storage structure data; wherein the storage structure data comprises at least one of the serial number of the bin and the hit frequency of the bin, and the storage overhead is remarkably reduced.