32results about How to "Optimize scheduling" patented technology

This invention relates to an automatic testing device and control method for a handheld terminal, comprising a frame composed of several supports and cover plates. The internal space of the frame is divided into a testing area and an electronic control area by partitions and supports. An electronic control module is located inside the electronic control area. A first control module is mounted on the side wall of the partition in the testing area, and a second control module is mounted on the first control module. The first control module is used to enable lateral movement of the second control module on the first control module. A third control module for changing the position of the handheld terminal is located at the bottom of the frame. The first control module includes a first synchronization belt. The advantages of this structure are that it solves the problems of low testing efficiency, large errors, complex structure, and testing of handheld terminals using only one or two control axes in existing handheld terminal testing methods.

The application discloses a kind of distributed energy two-way prediction optimization scheduling method and system, obtains historical data, historical environmental data, historical load data and historical scheduling strategy and carries out processing to data, is extracted and weighted fusion to the data after processing by the prediction model based on global feature and mutation feature, obtain first prediction result, by adaptive prediction model, obtain second prediction result for reverse distributed energy prediction solution, first prediction result and second prediction result are complex weighted fusion, obtain third prediction result, third prediction result is used to construct distributed energy optimization scheduling model and is solved, obtain scheduling result.This method effectively fuses environment, load, scheduling three, adopts two-way prediction to further improve the accuracy of distributed energy prediction, and optimization scheduling is established on the basis of prediction, so that the overall scheduling of massive distributed energy is more optimized.

The present disclosure relates to cell processing technology. As an example, a cell processing system can include a plurality of sample processing devices configured to process patient samples and a plurality of readers associated with the plurality of sample processing devices, respectively, wherein each reader is configured to read information from a tracking device associated with a respective patient sample. The system can also include a controller that uses information from the readers to provide an estimated completion time for a patient sample based on availability of the sample processing devices.

The application provides a kind of expressway emergency response method and system based on management and control unit, by obtaining the event logic knowledge network of expressway emergency event and the driving event data in the control unit monitoring flow, the knowledge vector data of each control unit driving event in multiple emergency response stages with logical time sequence order can be systematically analyzed and processed. By fusing the initial knowledge vector data of each emergency response stage and the prior transmission knowledge vector data, more accurate and comprehensive transmission knowledge vector data is generated, and the corresponding response scheme of each emergency response stage is determined. This method not only improves the accuracy and efficiency of emergency response, but also optimizes the allocation and scheduling of emergency resources by determining the priority information of candidate control unit driving events. Finally, according to the priority information of each control unit driving event, the disposal event corresponding to the expressway emergency event can be quickly and accurately determined.

This invention discloses a multi-dimensional indicator evaluation and automatic grading system for brand promotion tasks, relating to the field of brand promotion technology. It includes a data processing module for acquiring task feature data from a promotion task database, including dynamic features such as target audience segmentation, channel selection, and budget allocation. The module removes duplicate records and missing values ​​through data cleaning techniques and uses standardization techniques to convert the feature data into a structured feature dataset with a mean of 0 and a variance of 1, resulting in a structured feature dataset. This multi-dimensional indicator evaluation and automatic grading system for brand promotion tasks enables intelligent grading, optimized scheduling, and dynamic adjustment of promotion tasks, improving task execution efficiency and resource utilization, and providing more accurate decision support for promotional activities.

A multifunctional intelligent meter reading device comprises a meter reading module and a switching module. The meter reading module comprises a shell and an image acquisition unit. The image acquisition unit is arranged in the shell, and the first surface of the shell is provided with a first hole corresponding to the image acquisition unit in position and an annular part surrounding the first hole. The switching module is provided with a central channel and an adhesion surface. The adhesion surface is arranged at one end of the switching module, and the other end of the switching module is detachably arranged on the annular part. And the switching module is fixed on the target energy meter through the adhesion surface, so that the central channel is communicated with the first hole.

Embodiments of the present application provide a channel state information feedback method, device, communication equipment and storage medium. The method comprises: a terminal device sends first information to a network device, wherein the first information at least comprises: indication information of a channel state information (CSI) feedback method, or error information of different CSI feedback methods and the number of bits required for CSI feedback, or the number of bits required for CSI feedback corresponding to a CSI feedback method meeting a requirement.

The application discloses a kind of methods for evaluating the water quality of pipe network in the water supply area of water supply plant, comprising determining water quality turbidity and bacterial count in monitoring period after water source switching, treatment process or treatment parameter adjustment of water supply plant;Inquire turbidity and bacterial count in monitoring control period before water source switching, treatment process or treatment parameter adjustment;Then calculate the average value of turbidity and bacterial count in monitoring period and control period, calculate turbidity-bacterial colony weighted value;Then according to formula, the water quality score in monitoring period and monitoring control period is determined respectively;Finally, according to the difference between the water quality score of monitoring period and monitoring control period, as the judgment basis for the effect of water plant process parameter adjustment, process improvement, water source switching, provide accurate basis for water plant process parameter optimization, fine management, process improvement status, etc., achieve the goal of water plant process management with pipe network water quality as target.

This invention discloses a State of Charge (SOC) display system and method for unmanned logistics vehicles, belonging to the field of battery management technology for unmanned vehicles. The system includes: a vehicle controller, relays, a gateway, and a battery management system. When the vehicle controller and battery management system receive fast charging / slow charging / driving signals, the relay switches close, the gateway starts working, and forwards the data to the backend management system. When the vehicle controller and battery management system receive a driving signal, the backend management system displays the current SOC and driving status. When the vehicle controller and battery management system receive fast charging / slow charging signals, the backend management system displays the current SOC, charging status, charging time, and estimated full charge time. If the fast charging / slow charging / driving signal is lost, the backend management system displays the last received SOC and the vehicle's offline status, flexibly displaying information such as vehicle SOC, vehicle status, charging time, and estimated full charge time, achieving visualized monitoring of vehicle status and the charging process.

This invention relates to the field of data processing technology, specifically to an artificial intelligence-based production line scheduling optimization method. The method obtains the adjustment time and corresponding change magnitude based on the data change characteristics of parameter adjustment curves; it obtains the process difference significance based on the distribution characteristics of the adjustment times of parameter adjustment curves for all orders under the same process and the change magnitudes of all adjustment times; it obtains the target process based on the difference significance of all processes; and it obtains the comprehensive difference degree based on the difference characteristics of the parameter adjustment curves of the target process between different orders. This invention clusters all orders based on the comprehensive difference degree and order production time to obtain different order clusters; and it schedules and allocates production lines based on all order clusters, which can reduce equipment wear and tear and improve production efficiency.

The utility model discloses a multifunctional auxiliary law enforcement stick relates to law enforcement stick technical field, including inner stick body, is cylindrical, outer stick body, coaxial movable sleeve is established in the outer inner stick body, handle is fixedly connected with the first end of inner stick body, outer stick body with handle rotation is connected, still be equipped with the anti -drop rope on the handle, mode switching mechanism is arranged in the inside stick body for selectively switching the strike mode of law enforcement stick, mode switching mechanism includes. The utility model discloses through the innovative mode switching mechanism, will the cone point, needle point, round point three different forms of strike end integration in single stick body, and law enforcement personnel can cope with the broken window, precision control, large -area intimidation etc. multiple tasks without changing equipment, greatly improved the adaptability and law enforcement efficiency of equipment.

Embodiments of the present application provide a kind of air-based equipment cluster cooperative control method, electronic equipment, storage medium and program product, related to air-based equipment cluster control technical field, the method comprises: according to the unexplored unit on exploration map, select the target exploration position to be distributed to multiple air-based equipment, according to the cost of each air-based equipment to reach each target exploration position, obtain the distribution exploration position distributed to each air-based equipment in multiple target exploration positions, after the unit of exploration map is all explored, according to multiple user equipment positions on exploration map, select the target coverage position to be distributed to multiple air-based equipment, according to the cost of each air-based equipment to reach each target coverage position, obtain the distribution coverage position distributed to each air-based equipment in multiple target coverage positions, control air-based equipment moves to distribution coverage position.The embodiments of the present application avoid repeated exploration or omission exploration, and improve the pertinence of communication signal coverage.

The utility model relates to the field of water conservancy equipment, and discloses an ecological flow automatic adjusting and discharging device which comprises a gate frame, a gate plate is arranged in the gate frame, an automatic adjusting mechanism connected with the gate plate is arranged on the top face of the gate frame, and a mounting shell is fixedly mounted on the top face of the gate frame. When the small gear rotates, the two adjusting rods can be driven by the racks to move in the opposite directions, the two ultrasonic water level gauges can be conveniently adjusted to proper positions so as to monitor the water levels of the upstream and the downstream of the gate, and when a person reversely rotates the small gear, the two ultrasonic water level gauges can be close to each other so as to monitor the water level of the gate. And through the arranged control box body, the water flow meter, the ultrasonic water level gauge and the screw hoist, the operation mode of the gate can be intelligently adjusted in a linkage mode in the non-flood season and the flood season so as to ensure that the instantaneous water level change can be coped with in time, and automatic adjustment and discharge of the ecological flow can be achieved.

This invention belongs to the field of photovoltaic power generation control technology and discloses a method for partitioning distributed photovoltaic clusters in a regional distribution network. It calculates the electrical distance between nodes based on a frequency-active power sensitivity matrix and obtains the electrical distance matrix. An optimized initial centroid is obtained using the PSO algorithm. Based on the initial centroid, the K-means algorithm is applied to perform cluster analysis on the nodes of the distribution network, completing the cluster partitioning of energy storage nodes. Using energy storage nodes as centroids, the remaining photovoltaic nodes without energy storage and load nodes are further partitioned into clusters. A comprehensive performance index is obtained by weighting three indicators: active power balance, energy storage balance, and modularity. The partitioning scheme with the highest comprehensive performance index is considered the optimal cluster partitioning. This invention uses the energy storage area as the center to partition distribution areas containing distributed photovoltaics into clusters, providing necessary inertia and frequency support for the power grid.

The application discloses a residual attribute prompt driven detection and incremental learning method for unknown scattering objects, aiming to solve the problems of missing detection, false detection and lack of self-learning ability of existing inspection on training set outside scattering objects. When the inspection vehicle or unmanned aerial vehicle enters the working area, start the visible light camera to collect real-time video stream; use the context residual learning module to detect the abnormal area of the video image, generate the residual energy graph to locate the potential unknown scattering object; based on the shape, texture and reflectivity statistics of the candidate frame area, construct the attribute vector and automatically generate the descriptive semantic prompt word, the prompt and the preset word library are fused through the gate weight to drive the open visual-linguistic segmentation, output the boundary information and semantic label of the scattering object; through the adaptive incremental learning module, the new detection sample is updated and knowledge playback with few samples, realizing the dynamic expansion and continuous evolution of the knowledge base. The application realizes the discovery of unknown targets through residual detection, completes semantic recognition and boundary extraction through open segmentation, and continuously expands the detection category through adaptive incremental learning, constructs a 'discovery-recognition-learning' closed loop mechanism, thereby significantly improving the processing ability of road inspection on unknown scattering objects in complex environment.

The invention discloses an intelligent stereoscopic warehouse system and method based on a laser demarcation device, and belongs to the technical field of intelligent warehousing. The system establishes a high-precision space coordinate system for a warehouse through a space reference network formed by fixed laser demarcation devices; the mobile device visually perceives the network to realize submillimeter-level accurate positioning, scans the goods allocation by using a laser demarcation device carried by the mobile device, and perceives the state of the goods allocation in a non-contact manner; the central processing system is integrated with a digital twinning technology, inventory can be managed, and warehouse structure deformation can be monitored by analyzing long-term change of reference laser. The problems that a traditional stereoscopic warehouse is large in positioning accumulative error, goods location sensing depends on a large number of sensors, and the self-calibration capability is lacked are solved, and the precision, reliability and intelligent level of the system are remarkably improved.

The invention relates to a rail station shared bicycle classification scheduling method based on parking position perception, and the method comprises the steps: monitoring a shared bicycle parking region around a rail station, and obtaining the number, states and operator types of shared bicycles around the rail station in real time through a pre-trained parking position perception model; determining a corresponding operation strategy according to the number and the state of the shared bicycles and the types of operators to which the shared bicycles belong and in combination with the station types of the rail stations; according to the operation strategy, scheduling demands of shared bicycles around the rail station are predicted in real time, and scheduling suggestions are generated; and according to the generated scheduling suggestion, carrying out classified scheduling on the shared bicycles around the rail station. According to the method, efficient classified management and balanced distribution of the shared bicycles are realized through accurate perception and intelligent scheduling, the resource utilization efficiency and the user experience are remarkably improved, the operation cost is reduced, and the urban traffic resource allocation is optimized.

The application discloses a method and device for wireless communication. The first node sends a first report, and the first report indicates that the idle data rate capability is a first data rate, and the idle data rate capability is for a first inference configuration. The above method optimizes resource allocation, improves resource utilization and transmission efficiency, and ensures the QoS of services.

The invention provides a steel production method and system and electronic equipment, and the method comprises the steps: obtaining a plurality of to-be-executed heat numbers and a steel grade corresponding to each to-be-executed heat number, sorting the plurality of to-be-executed heat numbers based on the steel grade numbers to obtain a casting plan, and generating a steel making operation plan based on the steel production casting plan, steel production is carried out according to the steel production steelmaking operation plan, the execution sequence of the to-be-executed heat numbers is formulated based on the steel trademarks corresponding to the to-be-executed heat numbers, production scheduling and scheduling of the casting plan are optimized, actual execution of steelmaking production is guided, quality control of the production process is strengthened, and the production efficiency is improved. And the quality loss in the production process can be effectively reduced.

The invention relates to a cloud side end collaborative intelligent monitoring platform for a container yard and a scheduling method. The platform adopts a three-layer architecture in which a terminal sensing layer, an edge computing layer and a cloud intelligent layer are coordinated. The terminal layer is responsible for multi-source data acquisition; the edge layer is responsible for regional data fusion and real-time processing to realize low-delay control; the cloud is responsible for global modeling, macroscopic optimization and model training. The scheduling method comprises a task receiving and analyzing step, a cloud global pre-scheduling step, an edge local real-time scheduling and dynamic optimization step, a terminal instruction execution and state feedback step and a cloud learning and model iteration step. According to the platform disclosed by the invention, efficient aggregation, processing and intelligent application of data are realized by constructing a'cloud-edge-end 'three-layer cooperative computing architecture, so that the real-time performance and accuracy of global situation awareness of the storage yard are improved, equipment scheduling and path planning are optimized, and finally the purposes of improving the working efficiency of the storage yard, reducing the operation cost and enhancing the safety are achieved.

This invention discloses a method for the coordinated optimization of material flow and energy flow and carbon emission management in steel enterprises. The method includes the following steps: constructing a network model of material and energy flow in steel enterprises based on graph theory; introducing a dynamic adjacency matrix, with matrix elements quantitatively representing inter-process material / energy flow, energy efficiency parameters, and time delay characteristics; constructing an energy flow balance equation based on the adjacency matrix, aiming to minimize total energy consumption and maximize residual energy recovery rate; using an improved genetic algorithm to solve for the optimal scheduling scheme, dynamically matching production plans with energy supply; constructing a dynamic accounting model embedding process-level carbon emission factors, automatically generating carbon emission reports through real-time collection of EMS data; and providing carbon reduction strategies in conjunction with carbon quota prediction. This method can achieve accurate description and quantitative characterization of material and energy flow in steel enterprises, optimize energy scheduling, accurately calculate carbon emissions, and realize integrated management of energy and carbon emissions.

The application relates to the field of intelligent decision-making, and discloses an intelligent scheduling method for vehicle insurance field work, which comprises the following steps: obtaining historical vehicle insurance orders, querying vehicle insurance locations and vehicle insurance times of the historical vehicle insurance orders, and extracting vehicle insurance features of the historical vehicle insurance orders according to the vehicle insurance locations and the vehicle insurance times; calculating a spatial distance matrix and a time distance matrix between road section nodes in the vehicle insurance locations according to the vehicle insurance features; calculating space-time densities of the road section nodes in the vehicle insurance locations according to the spatial distance matrix and the time distance matrix, clustering road section nodes with space-time densities greater than a preset threshold, and obtaining a plurality of node clustering centers; when the road section node density in the plurality of clustering centers is reachable, the road section nodes are merged to obtain a plurality of merged clustering centers, a road section density distribution diagram of the vehicle insurance location is constructed based on each merged clustering center, and a scheduling personnel distribution scheme of the vehicle insurance location is constructed according to the road section density distribution diagram. The application can improve the timeliness of vehicle insurance field work scheduling.

The utility model relates to the technical field of cable hoisting, in particular to a cable hoisting circulating traction system and cable hoisting equipment, a first anchor, a second anchor, a first cable bent tower and a second cable bent tower are respectively arranged on a shore I and a shore II, a crown block device is arranged on a bearing cable in a sliding manner, one end of the bearing cable is anchored with the first anchor, and the other end of the bearing cable is anchored with the second anchor. The other end is anchored with the second anchor through the first cable bent tower and the second cable bent tower in sequence; the traction device comprises a traction driving mechanism and a traction cable, the first end of the traction cable is connected with the first anchor through the first anchor, the first cable bent tower and the first end of the crown block device, and the second end of the traction cable is connected with the second anchor through the first anchor, the first cable bent tower, the second cable bent tower, the second anchor and the second end of the crown block device; the traction driving mechanism can drive the crown block device to slide along the bearing cable through the traction cable. According to the utility model, the crown block device is pulled to move back and forth through the circulation of the single pulling rope, so that the safety risk of forced opposite pulling caused by unsmooth command signals during simultaneous traction on both banks is overcome.

The invention discloses a data packet flow control method and system, and the method comprises the steps: obtaining the real-time state information, including bandwidth, delay, packet loss rate and flow distribution, of a network; according to the real-time state information, an intelligent algorithm is adopted to analyze and predict a future flow change trend; according to a prediction result and application requirements, dynamically adjusting flow control parameters, and adopting a flow control strategy including but not limited to a token bucket, a leaky bucket or an adaptive control strategy; aiming at burst traffic, a priority scheduling algorithm is adopted to ensure that data packets with high real-time requirements are transmitted preferentially; the change of the network state is monitored in real time, the control strategy is periodically optimized and adjusted, and a response is quickly made and the sending rate is adjusted when network congestion or bandwidth fluctuation occurs; according to the data packet flow control method and the control system thereof, by introducing an intelligent adaptive flow control mechanism, efficient and real-time network flow scheduling is realized, the use of network resources is optimized, and flexible network topology adaptability is provided.

This application relates to the field of artificial intelligence technology, and in particular to a method and system for full lifecycle management based on a multi-dimensional AI evaluation model. The method includes: collecting industrial data from intelligent manufacturing equipment and preprocessing the industrial data; inputting the preprocessed industrial data into a multi-dimensional AI evaluation model to obtain multi-dimensional scores, and fusing the multi-dimensional scores to obtain a comprehensive data trust score; implementing flow control of industrial data throughout its entire lifecycle based on the comprehensive data trust score; collecting feedback indicators of the implementation effect of industrial data at each lifecycle stage, and adaptively iteratively updating the multi-dimensional AI evaluation model based on these feedback indicators. This application addresses the issues of single-dimensional industrial data evaluation, lack of value-driven approaches in full lifecycle management, and the lack of dynamic adaptive capabilities in the model.

The embodiment of the invention provides a network side node, user equipment, a method executed by the user equipment and a storage medium, and relates to the field of artificial intelligence. The method comprises: receiving a sub-band sounding reference signal (SRS) from a first UE, the sub-band SRS being an SRS sent by the first UE using a sub-band in a full frequency band; acquiring a full-band frequency selective fading (FSF) trend corresponding to the first UE; determining a full-band SRS channel of the first UE based on the full-band FSF trend and the sub-band SRS; and executing uplink / downlink multi-antenna system scheduling based on the full-band SRS channel. Optionally, the method performed by the electronic device may be performed using an artificial intelligence model.

The invention relates to a phase modifier optimal configuration method based on short-circuit ratio improvement. The method comprises two stages: in the first stage, the position and the basic capacity of the phase modifier are optimally configured by taking the improvement of the short-circuit ratio of the wind power plant as a core constraint, and in the second stage, the configuration capacity of the phase modifier is corrected by taking the transient overvoltage safety as a key constraint, and an improved genetic simulated annealing algorithm is introduced for optimization solution. Taking the minimum configuration capacity of the phase modifier as a target, comprehensively considering the wind power plant, the overall short-circuit ratio, the short-circuit ratio balance degree constraint, the phase modifier configuration number constraint and the power flow constraint, and completing the first-stage phase modifier optimization configuration to improve the power grid strength of the wind power plant. And in combination with the optimal configuration result of the phase modifier in the first stage, constructing a wind power plant transient overvoltage suppression-based phase modifier capacity correction optimization model, solving the model by using an improved genetic simulated annealing algorithm, and determining the correction capacity of the phase modifier. The method is effective for improving the voltage supporting capacity of the wind power plant and suppressing transient overvoltage.

The utility model relates to a tunnel wall structure fault inspection module, and belongs to the technical field of track detection equipment. The tunnel wall structure fault inspection module comprises an inspection vehicle body, an acquisition box, an outer cover, a camera, a light source, a heat dissipation plate, a positioning pin and a hasp, wherein the acquisition box is detachably mounted on the inspection vehicle body; the outer cover is mounted on the collection box, and a plurality of glass windows are arranged in the circumferential direction of the outer cover; the camera and the light source are arranged in the outer cover and are in one-to-one correspondence with the glass window; the heat dissipation plates are installed on the two opposite sides of the outer cover. The positioning pin is mounted on one side, close to the collection box, of the inspection vehicle body, a positioning hole is formed in the collection box, and the positioning pin is inserted into the positioning hole; the hasp is installed on the side wall of the inspection vehicle body. Therefore, according to the tunnel wall structure fault inspection module, the inspection vehicle body and the collection box are separately arranged, so that dispatching of the inspection vehicle body and the collection box is facilitated, the collection box is positioned through the positioning pin, and the hasp is clamped to the fixing hook, so that the inspection vehicle body and the collection box are convenient to assemble and disassemble.

This invention relates to a patient scheduling system for a hospital emergency room. An initial assessment scheduling module classifies admitted patients by urgency level. When medical resources are strained, it compares historical emergency records and simulates pre-treatment interventions based on similar cases. Simultaneously, it constructs a waiting queue containing patients at different treatment stages and predicts the impact of adding a patient to the waiting queue on the patient themselves and other patients in the queue. A secondary assessment scheduling module, after the patient receives formal intervention, schedules nurses to perform corresponding examinations and constructs a secondary examination result vector. A comprehensive assessment module combines the urgency level and the secondary examination result vector, using a pre-trained model to obtain the final patient classification, providing a basis for subsequent treatment scheduling. This invention, through pre-intervention and predictive dynamic ranking, effectively utilizes fragmented doctor time, optimizes emergency room resource scheduling, significantly shortens patient waiting time, and improves emergency efficiency and treatment success rate.