160results about How to "Efficient configuration" patented technology

The invention relates to the technical field of logistics transportation scheduling, in particular to a logistics management system based on intelligent scheduling, which comprises a data acquisition module, a demand analysis module, an intelligent scheduling module, a path planning module, a monitoring and feedback module, an optimization module and the like. The data acquisition module is used for collecting information such as goods, vehicles, storage, customer demands and traffic road conditions; the demand analysis module predicts logistics demands by using a time sequence analysis or machine learning algorithm; the intelligent scheduling module adopts a greedy and dynamic programming mixed algorithm to allocate resources; the path planning module calculates an optimal path according to road conditions and starting and ending points; the monitoring and feedback module monitors logistics parameters in real time and feeds back abnormity; and the optimization module optimizes the scheduling scheme according to the fitness function based on the genetic algorithm. According to the invention, data and resources of all links of logistics are effectively integrated, accurate demand prediction, efficient resource configuration, transportation path optimization, real-time monitoring feedback and overall performance improvement of the system are realized, the logistics cost is significantly reduced, and the transportation efficiency and the service quality are improved.

The invention discloses an intelligent logistics system based on optimal scheduling, and relates to the field of logistics management, and the system comprises the steps: arranging environment sensors at key nodes of a logistics network, and transmitting collected real-time data to edge computing equipment for preprocessing; analyzing the preprocessed data by using a deep learning model, and predicting an environment change trend in a non-period of time; dynamically adjusting a logistics scheduling strategy based on the prediction result; after receiving the adjusted scheduling strategy, defining a state space, an action space and a reward function of the logistics system; training a reinforcement learning algorithm model, and continuously optimizing a decision strategy through interaction with the environment; and calling the reinforcement learning model through an API interface to make a real-time decision, and generating an optimal scheduling scheme. According to the invention, by integrating environment perception, deep learning prediction, adaptive scheduling and reinforcement learning, the defects of an existing intelligent logistics system in the aspects of environment perception, prediction and dynamic scheduling optimization are overcome, and the intelligent level and operation efficiency of logistics management are significantly improved.

The invention discloses a joint beam forming optimization method for an RIS auxiliary low-altitude communication system. The problem of performance bottleneck caused by interaction of active beam forming and passive beam forming is solved by adopting a genetic algorithm based on a dynamic adaptive theory. Aiming at the limitation of a standard optimization method, a hybrid strategy of genetic algorithm optimization and a full-connection neural network is explored, and intelligent collaborative setting of system parameters is realized. Simulation results show that the hybrid algorithm not only simplifies the calculation process to obtain the optimal network parameters, but also effectively optimizes the system structure by dynamically adjusting the RIS reflection configuration. On the basis, the signal transmission quality is improved, interference is reduced, and it is guaranteed that the RIS-assisted low-altitude unmanned aerial vehicle intelligent communication system stably and efficiently operates in a complex wireless transmission environment.

The invention relates to the technical field of digital video devices, in particular to a digital video device control method and device. The method comprises the following steps: acquiring digital monitoring data, performing real-time scene acquisition and dynamic region optimization according to the data, and generating optimized dynamic region data; video frames are read based on the dynamic region optimization data, and abnormal behavior analysis and behavior intention evaluation are carried out; calculating the complexity of monitoring behaviors by combining video frame data and behavior intention data, and evaluating resource consumption increase; the processing bottleneck is evaluated according to the resource consumption growth data, and the processing capability attenuation analysis is carried out, so that the monitoring device is adjusted, and the system performance is optimized; according to the method, the resource allocation and processing capability of the video device is dynamically adjusted through real-time analysis and processing of monitoring data. According to the invention, the digital video device is adjusted, so that the prediction identification of the digital video device is more accurate and efficient.

The invention relates to an operation method of an unattended intelligent mobile emergency cabin. Comprising the steps of system initialization, material information configuration, authority verification, order generation, material warehouse-in and warehouse-out, inventory monitoring, intelligent prediction, decision support, data processing and synchronization and the like. Various parameters are obtained and configured through the system configuration module, material information is managed through the material detail directory tree module, accuracy of access authority is ensured through the face recognition and authority verification module, and automatic order generation and inventory updating are achieved through the automatic order generation and inventory updating module. A gravity sensing unit is used for monitoring warehouse-in and warehouse-out of materials, an inventory alarm and decision-making auxiliary module is used for monitoring an inventory state and sending an alarm signal, an intelligent prediction unit is used for predicting a material use trend and generating a replenishment plan, and finally data processing and synchronous management are realized through a data processing module. Manual operation is reduced, management efficiency is improved, timeliness and reliability of material supply are ensured, and the method is suitable for the fields of electric power engineering and the like.

The invention belongs to the field of ocean engineering and floating body structures, discloses a modularized movable variable-structure floating body platform and an operation method thereof, and is suitable for multi-scene application of short-term or temporary operation on the sea. In the towing process of the platform, chain type arrangement is adopted, all floating body units are connected through spherical hinge connectors, water resistance is effectively reduced, towing efficiency is improved, and safe transfer is achieved through a tugboat and an auxiliary boat. After the platform arrives at a target area, the platform flexibly adjusts the floating body units through the tugboats, the auxiliary boats, the mechanical arms and the connecting rods, chain type arrangement is changed into an array type structure, stable multi-column arrangement is formed, and different operation requirements are met. Due to the modular design, the platform has high expansibility and is convenient to maintain and recombine. The marine floating body platform is flexible, low in cost and environmentally friendly, has high wind wave resistance and wide application prospects, and is particularly suitable for various temporary marine operations such as marine monitoring, equipment installation and marine emergency.

The invention belongs to the field of intelligent manufacturing, and provides an intelligent recommendation method and system based on a shared robot, and the method comprises the steps: receiving a picture and a processing demand provided by a user; determining the processing attribute of the target workpiece according to the picture; determining a processing sub-task according to the processing attribute; determining an optimal shared robot combination according to the processing subtasks and the processing requirements; and displaying the optimal shared robot combination to the user.

The invention discloses an ITSS operation and maintenance resource configuration optimization method and system. The method comprises the following steps: firstly, establishing a network node model of operation and maintenance resources to be allocated; constructing a constraint model of the operation and maintenance resources to be allocated according to the constraint conditions of the operation and maintenance resources to be allocated; determining a to-be-allocated operation and maintenance resource configuration model based on the to-be-allocated operation and maintenance resource network node model and the to-be-allocated operation and maintenance resource constraint model; according to the to-be-allocated operation and maintenance resource configuration model, obtaining an initial configuration scheme of optimal configuration of to-be-allocated operation and maintenance resources and a resource configuration deviation matrix; and according to the initial configuration scheme and the resource configuration deviation matrix, obtaining a target configuration scheme for optimal configuration of the operation and maintenance resources to be allocated. Through the systematized and modeled operation and maintenance resource configuration optimization method, efficient, accurate and flexible configuration of the operation and maintenance resources is realized, and the method has remarkable effects of improving the operation and maintenance service quality, reducing the cost and enhancing the enterprise competitiveness.

The invention discloses an optimal locating and sizing planning method for an energy storage system and distributed power generation. The method comprises the following steps: representing the condition of installing an energy storage and distributed power supply in each node in a topological graph of a power system through a decision vector; establishing an admittance matrix according to the topological graph of the power system, and then performing conversion to obtain an impedance matrix of the nodes; and by taking the lowest operation cost as an objective function and combining constraint conditions, optimizing decision vectors by combining sensitivity analysis of an impedance matrix and a simulated annealing algorithm to obtain an optimal locating and sizing scheme of the energy storage system and distributed power generation. According to the method, the overall operation environment of a power grid and physical limitations of equipment are more considered, including consideration of the capacity of a transformer, and it is ensured that the safe operation range of the transformer is not exceeded while BESS and DG are increased; greater flexibility is provided, and the number and scale of energy storage and power generation facilities are allowed to be dynamically adjusted.

The present invention discloses a method and device for automatic configuration of a load balancing device, which belongs to the field of network technology. The method includes the following steps: obtaining load balancing planning information; extracting data center network area, load balancing device and IPv4 / IPv6 planning information and parsing their corresponding relationship, and forming a network matrix in combination with the current status of financial services; setting a load balancing demand template, receiving and sorting out load balancing configuration requirements; remotely connecting to a load balancing device and reading device configuration, parsing existing device configurations and sorting them out by categories; matching the load balancing configuration requirements with the network matrix, incrementally and automatically generating configuration command lines or API interface change templates, and obtaining the final load balancing configuration; remotely connecting to each load balancing device in the data center and issuing the final load balancing configuration. The present invention can concisely and efficiently complete the load balancing configuration work, improve the efficiency and accuracy of load configuration, and ensure the security of the financial cloud data center.

The invention discloses a dynamic traffic distribution and signal control combined optimization method, and belongs to the field of intelligent traffic. The method specifically comprises the steps that firstly, a road section impedance function is constructed, node impedance is introduced to obtain an intersection impedance combination function, and the intersection impedance combination function is optimized through the traffic flow, density and speed relation based on dynamic adjustment parameters, vehicle type differences, weather conditions and traffic flow speed to obtain a combination optimization traffic impedance model; and solving the combinatorial optimization traffic impedance model by using a particle swarm algorithm to output a traffic distribution scheme. According to the method, dynamic traffic distribution and adaptive signal control are integrated, the road network emergency response capability is improved, traffic prediction and signal regulation and control synchronization is realized, and an accurate impedance model is introduced to dynamically adapt to driver preferences, so that congestion is relieved, and travel time and resource allocation are optimized.

The invention relates to a parameter configuration method and device in a multi-computing-cluster environment, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: determining a value space of each database parameter in a to-be-configured database; according to the plurality of query tasks, determining a performance index function for the to-be-configured database; traversing each value point in the value space, and executing a plurality of query tasks according to database parameters represented by the traversed value points to obtain execution index scores of performance index functions under the database parameters represented by the traversed value points; and determining a target value point in the targeted value space, and performing parameter configuration on the to-be-configured database according to database parameters represented by the target value point. By adopting the method, the overall performance of the database can be improved, and meanwhile it is guaranteed that the computing clusters under different hardware configurations can play the optimal performance.

The invention provides a knowledge graph-based remote control instruction construction method and management system for a low-orbit flyer cluster, designs an instruction metadata model based on knowledge ontology, and realizes classification, treatment and semantic association of instruction elements by constructing a'concept layer-strength layer-instruction layer 'multi-level instruction generation mechanism. A business-driven instruction collaboration network concept is provided, and a multi-satellite, multi-system and multi-task collaboration instruction cluster generation mechanism oriented to a complex task scene is supported. Trial is carried out on the realized low earth orbit satellite remote control instruction generation and management system, and the feasibility of the method and the system is verified. According to the method, the flexibility and expandability of an instruction system are improved, support is provided for efficient configuration, generalization multiplexing, new instruction discovery, safety and reliability of future complex instructions, and deep exploration can be continued in future research work. The method is not only suitable for the field of low-orbit satellites, but also has reference significance for other satellite system networks.

The invention belongs to the technical field of whole vehicle detection and authentication, and particularly relates to a method for generating an optimal solution and a feasible solution of an actual measurement scheme for a multi-record declaration value, which comprises the following steps of: performing logic association classification on parameters according to enterprise record information to form an entry system, and generating an optimal solution and a feasible solution of the actual measurement scheme based on preset logic of the entry system in combination with a binding relationship; project configuration information can be obtained; project configurations which cannot be covered by a similar report are screened, the configurations needing to be actually measured are integrated, only parameters related to actually measured projects and parameters with multiple declaration values in results are reserved, final actually measured analysis configurations are formed, and an actually measured scheme which most meets the requirements is found out through step-by-step combined analysis; and traversing other entries to generate a complete actual measurement configuration. According to the method, the technical problem of how to quickly and efficiently formulate the optimal detection scheme for the recorded parameters and the existing video report by a vehicle production enterprise is solved.

The invention relates to a data processing method and device based on a low-power-consumption multi-core processor. The method comprises the steps that a register block is configured by multi-core processor data through a configuration network, and the register block sends a starting instruction to a data selector to start data transmission. After receiving the starting instruction, the data selector obtains data of the multi-core processor and determines first data participating in reduction, the first data is correspondingly stored in the FIFO register set according to the address of the multi-core processor, and storage information is obtained. And the control unit performs reduction operation on the first data according to the storage information to obtain a multi-core data processing result, and the multi-core data processing result is processed by the operation unit and then sent to the shared memory. By adopting the method, the memory access power consumption and delay in the reduction operation can be reduced under the condition that an instruction set is not changed.

The invention discloses a parking lot planning method based on real-time operation big data of a parking lot, and the method can dynamically optimize the use and management of the parking lot based on the real-time operation big data of the parking lot. Firstly, in combination with vehicle access time and direction data and operator mobile phone signaling data, a trip starting point and a trip ending point of regional traffic flow are accurately calculated, and accurate analysis of traffic flow modes and parking requirements is facilitated. And secondly, a space-time state model of the parking lot is constructed through real-time flow data, the utilization rate and the turnover rate of the parking spaces in different time periods can be reflected in real time, and the parking demand and the vehicle flow trend in the future are predicted, so that a scientific basis is provided for resource optimization configuration of the parking lot. And finally, performing path planning by using the real-time vehicle position, the destination and the predicted parking lot state data, dynamically adjusting the vehicle driving route, and optimizing the optimal path for the vehicle to arrive at the destination.

The present application relates to a data processing method and device based on a low-power multi-core processor. The method includes: the multi-core processor data is configured through a network configuration register group, and the register group sends an enable instruction to a data selector to start data transmission. After receiving the enable instruction, the data selector obtains the multi-core processor data and determines the first data involved in the reduction. The first data is stored in the FIFO register group according to the address of the multi-core processor to obtain storage information. The control unit performs a reduction operation on the first data according to the storage information to obtain a multi-core data processing result, and sends the multi-core data processing result to a shared memory after being processed by an operation unit. The use of this method can reduce the memory access power consumption and delay in the reduction operation without changing the instruction set.

The invention belongs to the technical field of intelligent manufacturing and industrial scheduling, and provides a high-altitude platform multi-test task production scheduling method based on a clustering algorithm and multi-objective optimization, and the method comprises the steps: automatically calculating the exclusive resource demands of all working condition points in a plurality of aero-engine test tasks based on a multi-parameter coupling model; for each task, dividing a plurality of work packages by adopting a clustering algorithm based on the multi-dimensional features containing exclusive resource requirements in the task; a multi-objective model of multiple optimization objectives is constructed, all the work packages are jointly sorted globally, and the optimization objectives comprise the equipment utilization rate; and finally, under the condition that constraint of resource capacity, mutual exclusion of test cabins and task continuity is satisfied, allocating an available tester and a continuous time window to each work package, and generating an initial production scheduling plan. According to the method, the production scheduling efficiency and the resource utilization rate are effectively improved, the plan robustness is enhanced, and the method is suitable for high-complexity aero-engine test scheduling scenes.

The embodiment of the invention discloses a configuration interaction method and device, equipment, a medium and a product, and the method comprises the steps: displaying a configuration interface for a target system, and the configuration interface comprises an instruction interaction region; in response to an interaction instruction received through the instruction interaction area, a dynamic configuration panel is displayed in the configuration interface, and the dynamic configuration panel comprises interaction configuration elements matched with the interaction instruction; and in response to a trigger operation for the interaction configuration element, displaying a visual display interface, and updating and displaying a rendering result of the target system in real time in the visual display interface so as to present a visual effect consistent with the interaction configuration element after the trigger operation. According to the technical scheme of the embodiment of the invention, efficient interaction of instruction-on-demand configuration element display-real-time feedback is constructed, and the accuracy and efficiency of configuration interaction are improved.

The invention discloses a cost optimization method, a cargo loading method and device and a cloud control center of a mine charging and battery swapping station. The optimization method comprises the following steps: firstly, obtaining a peak-valley-flat time period in the time-of-use electricity price of a power grid; then, judging whether the current actual time falls into the power utilization peak time period in the power grid peak-valley-flat time period or not: if the current time is not in the power utilization peak time period, directly charging a non-fully-charged preparation battery of the mine charging and battery swapping station; if the current time is in the power utilization peak period, determining whether to charge the non-fully-charged preparation batteries in the mine charging and battery swap station according to the relationship between the number of the non-fully-charged preparation batteries of the mine charging and battery swap station and the number of the low-electric-quantity mine cards; the low-electric-quantity mine cards refer to mine cards of which the residual electric quantity is lower than a second threshold value of battery charging and replacing. Through the method, the charging strategy can be flexibly adjusted, the electric power cost is effectively reduced, the economic benefit of mine operation is improved, and meanwhile reasonable utilization of resources and improvement of the operation efficiency are promoted.

The invention discloses a converter-free photovoltaic control method applied to a wind-light-storage hybrid energy system, which integrates photovoltaic power generation into a hybrid system by reducing the number of control loops and converters. The designed controller is suitable for a grid-connected system with wind energy and photovoltaic power as main power supplies, BESS as a secondary power supply and FC and an electrolytic cell as three-level power supplies. And through the combination of the pre-compensator and the integrator, the stability of the controller is enhanced, and the steady-state error is eliminated. In the proposed configuration, the GSC maximizes photovoltaic power generation, injects its power into the grid, while sharing the grid load with the RSC. By coordinating the control of the BESS and the fuel cell, the intermittent influence of wind energy and photovoltaic power generation is reduced, and redundant electric energy is used for hydrogen production of the electrolytic cell to support power generation of the fuel cell in adverse weather. And an energy management strategy is provided, so that BESS overcharging is avoided, intermittency and volatility are reduced, and stable power output and service continuity are ensured.

The invention provides a hard disk backboard and a server, the hard disk backboard is provided with a plurality of first connectors and a plurality of second connectors, and the hard disk backboard can be switched between a first working mode and a second working mode; in the first working mode, each first connector and each second connector are respectively used for electrically connecting different hard disks, and each hard disk is in communication connection with the mainboard through the first connector or the second connector; in the second working mode, the at least two first connectors are connected with the RAID chip in a matched mode, the other first connectors or the second connectors are used for being electrically connected with different hard disks respectively, the RAID chip is in communication connection with the corresponding hard disk through the corresponding first connector, and the RAID chip is in communication connection with the mainboard through the first connector. According to the hard disk backboard and the server, the expandability and flexibility of the system are improved, efficient management and configuration of the hard disk are achieved, and the effects of fault isolation, hard disk redundancy and stable performance are achieved.

The invention relates to the technical field of distributed storage, and discloses a distributed storage system with infinitely extensible capacity and performance and a storage method thereof.The distributed storage system comprises a special storage device cluster and further comprises a mobile device node pool composed of mobile devices in a company internal local area network; the dynamic node management and self-adaptive expansion mechanism is located in the data scheduling and management module and is closely integrated with the data scheduling and management module; and a data transmission protocol and an encryption mechanism. Through the synergistic effect of the data caching module and the preloading engine, the system significantly reduces the direct access to the special storage device cluster, and optimizes the data flow path. The data scheduling and management module dynamically adjusts a cache strategy, so that common data can be quickly read from a cache, and meanwhile, a preloading engine loads possibly needed data in advance according to a historical access mode. According to the mechanism, the data access delay is reduced, and the response speed and the overall performance of the system are greatly improved especially in the scene of high-concurrency requests.

The invention discloses an LED rental large screen rapid configuration system and method based on a UWB positioning technology, and relates to the technical field of LED display. Comprising UWB positioning labels, wherein each LED box body is provided with one UWB positioning label, and the UWB positioning labels are used for transmitting UWB signals; the UWB positioning base stations are arranged around the LED rental large screen installation area and used for receiving signals sent by the UWB positioning labels and calculating the position information of the labels; the central control unit is used for receiving the position data transmitted by the UWB positioning base station and automatically calculating the relative position relation of the box bodies according to a preset box body layout rule; the receiving card configuration module is used for automatically generating configuration information of a receiving card according to the position relation of the box body; the information is sent to each receiving card in a wired or wireless mode; and the LED box body comprises an LED display unit and a receiving card, and the receiving card is responsible for receiving and processing the configuration information and adjusting the working state of the LED display unit so as to realize correct image display.

The invention discloses a multi-agent-based space-time activity analysis and prediction method for urban empty nesters. Comprising the steps of collecting extrinsic features of community residents and constructing a space-time activity sand table, identifying urban empty-nest elderly people and staying points thereof, constructing a typical space-time activity chain of the urban empty-nest elderly people, constructing a multi-agent model of the urban empty-nest elderly people, simulating and screening demands of the empty-nest elderly people, and generating a public service facility layout optimization scheme. And the requirements of the empty nesters are visualized. According to the method, high-precision resident extrinsic features and high-resolution spatial data are acquired, and a multi-agent model is adopted to simulate and screen the demands of the empty-nest elderly, so that full-coverage, precise and multi-dimensional identification of the activity demands of the empty-nest elderly under an urban scale is realized; and a reliable basis is provided for perfecting urban community public service facilities and improving the life quality of old people.

The invention belongs to the field of sorting transmission lines, and particularly relates to a multi-sensor fusion sorting system and method based on vision, and the sorting system comprises a master control device, a sorting device and a transmission device; the master control device is used for mutually transmitting information with the transmission device and the sorting device, and controlling the transmission device and / or sending an instruction to the sorting device after receiving the information; and a sensor is carried on the sorting device. Compared with the prior art, various sensors are used in a fused mode, the tail end executing mechanism flexibly adapting to three-dimensional objects in different shapes is selected to achieve stable grabbing of the sorting assembly line, and the matched AGV carrying the multiple sensors can achieve autonomous path planning; and through cooperative communication with the portal frame on the assembly line for visual identification, the materials on the assembly line can be monitored and classified in real time, so that efficient sorting is further achieved, and automatic grabbing and automatic classification of the materials in different shapes on the transmission line are achieved.

The present disclosure provides a configurable file generation method, device, electronic device, medium and computer program product. The above method and device can be used in the field of big data technology. The configurable file generation method includes: obtaining m data tables, wherein each of the data tables includes a transmission field and transmission data corresponding to the transmission field, and m is an integer greater than or equal to 1; generating a corresponding data file according to each of the data tables, wherein the data file includes at least structural data and parameter data, the structural data is generated according to the transmission field, and the parameter data is generated according to the transmission data; editing each of the data files to obtain a fixed file; creating a submission file generation task, wherein the submission file generation task includes the number m of the fixed files in the submission file; generating the submission file according to the submission file generation task; and transmitting the submission file to the data receiving system.

The invention provides a heterogeneous multi-cloud resource pool arrangement method and a cloud resource management method and device.The arrangement method comprises the steps that for each target task of each cloud platform, calling relations among multiple related first APIs are arranged based on parameter information, so that the related first APIs are called to achieve the target tasks; wherein the target task is a task involved in cloud resource full life cycle management; based on the calling relation and the parameter information, packaging is carried out according to different types of the target tasks, and a second API interface corresponding to each type of target tasks is obtained; generating a first visual interface corresponding to each type of target tasks, and displaying the first visual interface to a user; wherein the first visual interface comprises an interaction control, so that a user calls the second API interface through the first visual interface to execute the target task. In this way, the functions of identification, arrangement and automatic management of heterogeneous multi-cloud resources, unified abstraction of cross-cloud resources and the like can be achieved.

The present application relates to a kind of 5G / 5G-A network slice resource allocation methods supporting high reliability low latency service and enhanced mobile bandwidth service coexistence, belong to mobile communication field.It includes: obtaining URLLC and eMBB service coexistence 5G / 5G-A network parameter information;Optimization target and constraint condition of minimum physical resource block usage are constructed;According to system model and optimization target, establish the hierarchical PPO model assisted by transfer learning, and design state space, action space, reward function and action space truncation mechanism;Pre-training and the parameters of the pre-trained resource allocation model are migrated to hierarchical PPO model;Hierarchical PPO model is trained, and network parameters are updated according to loss function until model converges, obtain the physical resource block allocation method for URLLC and eMBB service coexistence.The present application minimizes physical resource block usage while guaranteeing slice service quality, improves resource utilization.

The present application relates to the technical field of hardware layer design, and particularly relates to a hardware layer design method based on an embedded operating system, comprising the following steps: analyzing application program interfaces stored in a current hardware layer to obtain application program interfaces stored in the hardware layer configured by a current operating system; receiving a running task of the current operating system, and analyzing application program interfaces required by the running task to be configured; searching for the application program interfaces required by the running task to be configured in the application program interfaces stored in the hardware layer, and feeding back the searching process of the application program interfaces to a system user in real time; the present application can bring an intelligent hardware layer design method to the current embedded operating system, and in the step execution process of the method, the hardware layer intelligent design of the embedded operating system is realized by analyzing the application program interfaces existing in the hardware layer in real time.