72 results about "Management algorithm" patented technology

The invention relates to the technical field of oil and gas well management, in particular to an intelligent remote transmission control oil and gas well system based on the Internet of Things and multi-dimensional physical sensing feedback. Comprising a multi-dimensional sensor module; a 4G unvarnished transmission communication module and an intelligent remote decision module; the intelligent remote decision-making module is used for analyzing the collected data and generating a control strategy based on a self-adaptive gradient lifting decision-making tree algorithm; and the wide-temperature adaptive power supply module is used for providing continuous power supply for the system based on a multi-energy collaborative energy management algorithm and realizing energy optimization in an off-grid environment. By integrating multi-dimensional physical quantities such as pressure, flow, temperature and vibration, a multi-parameter coupled state space model is constructed, high-confidence real-time data input is provided for control strategy generation, limitation of traditional data processing on dimension coverage and feature extraction is broken through, and comprehensiveness and accuracy of gas well operation state evaluation are improved.

The embodiment of the invention relates to a multi-energy complementary coordinated control system and method based on multi-element energy storage, electronic equipment and a storage medium. And various data support optimization decisions of multiple stations are obtained through data fusion. And a decision generation scheme is optimized, the operation state and benefit analysis are displayed, and precise regulation and control of the station are realized. And configuring a management algorithm for the model, and setting boundary conditions and objective functions. The internal coordination supplementary logic plays a role in the aspects of active power adjustment, power grid frequency fluctuation and synchronous phase modulation. Through the means, the acceptance degree of the power grid to renewable energy sources is improved, so that the multi-energy complementary system can better respond to a power grid dispatching instruction, and energy resource optimization management is realized. And meanwhile, the stability and reliability of the power grid are enhanced, the economic benefit of the system is improved, and a powerful guarantee is provided for efficient operation of the multi-energy complementary coordination control system.

The presently disclosed technology provides methods and systems for optimally allocating power among workloads executing on a computer system through use of a power management algorithm. For example, according to the present technology a plurality of CPUs within a server can be divided into multiple groups according to application workloads. Workloads can be distributed to the CPUs as needed by a workload scheduler, and the workload scheduler can provide the CPU IDs to a power manager, enabling the power manager to optimize power settings. Each group of CPUs can be assigned an optimal power profile tailored to its respective situation.

The invention relates to the technical field of energy management, in particular to a hybrid power system energy management algorithm, which comprises a working condition prediction module, a dynamic weight distribution module and a hierarchical execution module, and is characterized in that the working condition prediction module is used for fusing vehicle networking data and vehicle-mounted sensor data and generating a multi-dimensional working condition prediction result in a future time period; the dynamic weight distribution module calculates dynamic weight coefficients of different optimization targets in real time based on the working condition prediction result, and generates an optimization problem description file containing weight coefficient constraint conditions; a rolling optimization layer unit in the hierarchical execution module receives the optimization problem description file and solves a global optimal power distribution reference in a fixed time window; the dynamic compensation layer unit generates a compensation correction item for dynamically adjusting a weight coefficient according to a deviation value between a global optimal power distribution reference and a current vehicle state; and the real-time control layer unit converts the compensation correction item into a power distribution instruction, and synchronously updates the weight coefficient of the dynamic weight distribution module.

The invention discloses a data transmission and control method and system based on a Beidou short message, and relates to the technical field of remote monitoring and communication, and the method comprises the steps: a Beidou slave station receives remote signaling and telemetering data, carries out the data processing of the received data, packages the data into a Beidou short message format, carries out the data transmission through a multi-mode command transmission protocol, and carries out the data transmission through a Beidou short message transmission protocol; the method comprises the following steps: receiving command data converted by a Beidou master station, monitoring a system in real time through a command execution state, feeding back an execution progress and state to the master station in real time, automatically executing a recovery process through a fault self-healing mechanism when data transmission is abnormal, and automatically adjusting data transmission frequency and power by utilizing a self-adaptive energy management algorithm, so as to realize real-time data transmission. And through the data transmission prediction model, predicting a data transmission demand, and adjusting a data refreshing strategy in advance. Through the adaptive energy management algorithm and the prediction model, the data transmission frequency and power are dynamically adjusted, the energy consumption is optimized, and the data transmission efficiency and real-time performance are improved.

The invention discloses an ultra-low power consumption pyroelectric infrared human body detector and a networking control method thereof. The detector comprises a detection module, a control module, a power supply module, a communication module, an interaction module and a dynamic power consumption management module, human body infrared radiation is detected based on the pyroelectric effect, and ultra-low power consumption operation is achieved by dynamically switching working modes. The networking control method is based on a BLE Mesh protocol, a self-adaptive topology management algorithm is used for optimizing routing, and efficient networking with intelligent equipment is achieved. The system solves the problems of high power consumption, large networking delay, high false alarm rate and the like of a traditional detector, and is suitable for the fields of smart home, intelligent security and protection and the like.

The invention discloses a scenic spot automatic driving yacht scheduling management algorithm. The system comprises a data acquisition and processing module, a distance calculation module, a comprehensive evaluation module, a scheduling decision module, a real-time monitoring and adjusting module and the like. The data collecting and processing module accurately obtains tourist demands and yacht state data and preprocesses the tourist demands and the yacht state data. The distance calculation module constructs a water area map model, and corrects the distance from the yacht to the boarding point in combination with water flow and wind direction factors. And the comprehensive evaluation module can evaluate the yachts in multiple dimensions and exclude unseaworthy yachts. And the scheduling decision module screens candidate yachts based on the results, selects an optimal scheduling scheme by using a weighted comprehensive evaluation method, issues an instruction and feeds back the instruction to tourists. The real-time monitoring and adjusting module monitors the state of the yacht in real time, quantifies and grades according to the task emergency degree, and adopts corresponding strategies according to different grades; the system can adapt to various scenic spot environments, significantly improves the scheduling efficiency, optimizes the resource utilization, enhances the tourist experience, and guarantees the reliable operation of the automatic driving yacht system in the scenic spot.

The invention provides a multi-language compatible algorithm scheduling platform and method, and the platform comprises a data collection module which is used for receiving basic information and algorithm files of different language algorithms based on an API interface, and converting the algorithm files into mirror image files according to the basic information based on a preset method; the algorithm deployment module is used for carrying out environment configuration on the algorithm container based on the basic information, carrying out isolated deployment on the mirror image file in the algorithm container based on an environment configuration result, and carrying out multi-dimensional management on different language algorithms subjected to isolated deployment; and the algorithm scheduling module is used for receiving a service demand based on the multi-dimensional management result, locking a target language algorithm based on the service demand, and performing scheduling operation on the target language algorithm based on an API interface. According to the method, different language algorithms can stably and reliably run in a deployment environment, the reliability of cross-language deployment is improved, and the reliability, stability and accuracy of multi-language algorithm scheduling are improved.

The invention belongs to the technical field of the vertical field, and particularly relates to a bid invitation file intelligent editing system based on a vertical model, which comprises a data acquisition module, a data processing module, a knowledge graph construction module and a bid invitation file generation module. The data acquisition module acquires project information and multi-modal data of a bid invitation project; the data processing module preprocesses unstructured files in the bid invitation knowledge base by using a TextRank algorithm and a BiGRU algorithm to generate structured data with dynamic weight tags; the knowledge graph construction module constructs a bid invitation knowledge graph based on a time sequence knowledge graph, an entity life cycle management algorithm and relation dynamic reasoning; the bid invitation file generation module generates a preliminary bid invitation file through a vertical generation model, and generates a final bid invitation file through multi-dimensional verification. According to the system, intelligent and efficient compilation of the bid invitation file is realized, and the compliance, integrity and standardization degree of the file are remarkably improved.

The invention relates to a switch cabinet with a built-in intelligent management and control system, through integration of a sensor network module, a data acquisition module, an intelligent processing module, a remote monitoring module and an active safety protection module, conversion from passive maintenance to active management and control is realized, and the switch cabinet is equipped with various sensors, so that the operation state of equipment can be monitored in real time; historical data are generated through timestamp records, and the intelligent processing module predicts the service life and the fault risk of the equipment in real time by applying a health management algorithm and a deep learning algorithm, identifies different fault modes and sends out an alarm signal; the active safety protection module comprises an electric power cut-off device, a temperature overrun protection unit and an emergency power supply unit, and can quickly cut off a power supply or start a cooling measure when abnormal parameters are detected, so that the equipment safety is ensured; and the intelligent level and the reliability of the switch cabinet are improved.

According to the lightweight communication encryption method and device among the multiple ECUs in the vehicle, a CAN frame encryption list is defined in each ECU in the whole vehicle, only CAN frames containing important signals are encrypted, and other CAN frames still adopt plaintexts for information interaction. Besides, in order to guarantee safety, a session key updating management algorithm is designed, in the algorithm, session keys are periodically and indirectly updated through random numbers of the main management node ECU, the random numbers are transmitted from the main management node ECU to other node ECUs through an advanced encryption algorithm, although operation of the advanced encryption algorithm is time-consuming at a time, the operation frequency is low, and the operation efficiency is high. And the overall influence on the computing power of the ECU is small. Therefore, not only can the advantages of simple and convenient information interaction and high efficiency among the ECUs in the vehicle be taken into consideration, but also the requirement of information security can be met.

The invention provides a power management method and system adapted to an extreme environment. Wherein a power management scheme is generated according to the environmental sensor data and the historical energy consumption record, and the power management scheme is used for adapting to an extreme environment; all the medical devices are classified according to first-aid priorities, a decision analysis algorithm based on multiple criteria is adopted to balance the function importance of the different medical devices and the current task demand, and an energy-saving optimization configuration table is generated; based on the energy-saving optimization configuration table, applying an adaptive fault prediction and health management algorithm to monitor the health state of the power supply system, and generating early warning information and maintenance suggestions; and according to the early warning information and the maintenance suggestion, real-time visual management of the power supply state of the medical treatment box is realized through a security encryption communication link, and a remote management mechanism is generated. According to the technical scheme provided by the invention, the power utilization stability and efficiency of the medical treatment box in an extreme environment are remarkably improved.

The invention discloses an improved trajectory extraction multi-maneuvering target tracking method, which comprises the following steps of: firstly, finishing long-time and continuous trajectory extraction of various targets including derivative targets, new targets and the like by adopting a labeled nearest neighbor trajectory management algorithm; then, introducing a multi-model thought, and proposing a multi-model Gaussian mixture probability hypothesis density filtering algorithm based on a jump Markov process; based on a tagged'nearest neighbor 'trajectory management algorithm and a multi-model Gaussian mixture probability hypothesis density filtering algorithm, a tagged jump Markov Gaussian mixture probability hypothesis density filtering algorithm is designed, and effective tracking and trajectory extraction of multiple maneuvering targets in a complex environment are realized. According to the method, the application scene of the Gaussian mixture probability hypothesis density filtering algorithm is expanded, the target trajectory can be accurately and effectively extracted in the face of a multi-target tracking scene including derivative target hypothesis, and the tracking precision under the complex condition is improved.

The invention discloses a medical information module big data-based low-energy-consumption single-chip microcomputer system, which comprises a hardware framework and a software framework, and is characterized in that the hardware framework is a single-chip microcomputer hardware platform, and the single-chip microcomputer hardware platform comprises a processor, a memory, a peripheral interface, a power supply and a resource sharing center; the resource sharing center is in electric signal connection with a centralized prescription checking module, a health follow-up visit module, a regional inspection module, a network electrocardio module, a disinfection supply module, a medicine distribution and supply module, a medical care scheduling module, an image cloud diagnosis module, a remote consultation module and an intelligent first-aid module in sequence; the software framework comprises a low-power-consumption management module and an RTOS management module. According to the scheme, the resource sharing center is controlled to build all doctor-patient network information modules, medical information data are collected in an omnibearing mode, the overall energy consumption of the system is effectively reduced through a low-power-consumption management algorithm, and the endurance time of related equipment is prolonged, so that medical information big data are continuously captured, and good two-way services are provided for doctors and patients.

The invention relates to the technical field of low-altitude economic meteorological safety and aircraft communication navigation monitoring service, and discloses a low-altitude flight service software and hardware platform integrated with a meteorological safety algorithm. Comprising a foundation platform (a vertical take-off and landing point / an airport and the like), a ground / satellite / and various private networks, an aircraft communication guiding and monitoring module, a low-altitude flight service software and hardware platform fused with a meteorological safety algorithm and the like. The method can effectively solve the flight safety problem of various aircrafts, provides a safe, scientific and accurate flight service early warning decision management algorithm scheme, and can be widely applied to the low-altitude economy industry. For example, project construction of low-altitude economic unmanned aerial vehicles / manned aerial vehicle foundation platforms (vertical take-off and landing points / airports and the like) and application of a low-altitude economic flight service platform in scenes such as electric power / petroleum / communication / chemical engineering / civil aviation airports / meteorological stations / forests and the like are expanded, and the market huge application value is extremely high.

The application particularly relates to a kind of asset performance analysis methods based on self-defined algorithm.The asset performance analysis method based on self-defined algorithm is through interface management algorithm factor, sets the mapping relationship of algorithm factor and collected data, and collects and stores algorithm factor data, presents algorithm factor index data in list mode;Algorithm formula is self-defined and set and legality check;Set early warning rule;If the data of current granularity has completed data collection in this period, then trigger algorithm scheduling;Algorithm calculation is carried out based on algorithm factor data;Automatic trigger early warning analysis, generate early warning message according to early warning rule, notify relevant person in charge.The asset performance analysis method based on self-defined algorithm solves the problem that analysis algorithm basic data cannot be quickly expanded, so that the expansion of basic data can be directly applied to algorithm, which can quickly realize the expansion and adjustment of algorithm, and also provides an effective means for the optimization and fine adjustment of algorithm.

Methods, apparatuses and systems for detecting and managing arc events during a plasma chamber process include receiving impedance data measured during a plasma chamber process, analyzing the impedance data to determine if an arc event is occurring during the plasma chamber process, and if it is determined that an arc event is occurring, an action is taken to suppress an arc of the arc event. In some instances, a machine learning model that has been trained to recognize when an arc event is occurring from received measurement data is used to determine if an arc event is occurring.

The invention relates to the technical field of three-dimensional reconstruction, in particular to a rapid three-dimensional reconstruction system based on deep learning, which comprises a data layer module used for inputting multi-view image data, configuring image sizes, calculating equipment parameters and performing read-write and management on output point clouds, grids and depth maps; the algorithm layer module is used for performing calculation based on a three-dimensional reconstruction algorithm, including depth estimation, point cloud generation, global alignment and grid reconstruction; the business logic layer module is used for coordinating all the modules to execute full-process automatic reconstruction and constructing a full process from multi-view image data input to model output; the presentation layer module is used for providing an interactive interface for the user; the communication layer module is in communication connection with the data layer module, the algorithm layer module, the business logic layer module and the presentation layer module and used for completing data transmission and state synchronization among the modules, and the problems that in the prior art, equipment cost is high, real-time performance is poor, efficiency is low and precision is insufficient are solved.

The invention discloses an algorithm library management system supporting visual arrangement of an algorithm model construction process. The algorithm library management system comprises an algorithm component management module, an algorithm component configuration module, an algorithm process arrangement module, an algorithm process operation module and an algorithm process log management module. The algorithm component management module is used for constructing and managing a full-process model algorithm component; the algorithm component configuration module is used for responding to a request of a user for setting specific parameters for each algorithm component in an algorithm model construction process; the algorithm process arrangement module provides a visual arrangement interaction mode, responds to the operation that a user drags algorithm components into a canvas, and connects the algorithm components according to a logic sequence through connecting lines to achieve data communication and transmission between the algorithm components. The algorithm process operation module is used for automatically executing algorithm components and resource scheduling according to the arranged logic sequence and completing execution of the whole algorithm model construction process; according to the method, a developer can construct and manage the algorithm model more efficiently and flexibly.

The invention provides a continuous casting machine management method and system, and the method comprises the steps: carrying out the communication with a PLC module of each function module of a continuous casting machine through an OPC server, and collecting the equipment information of each function module of the continuous casting machine and the operation data of each function module; acquiring equipment information of each functional module and operation data of each functional module through a database management system; analyzing the equipment information of each functional module and the operation data of each functional module, and generating a control instruction of each functional module of the continuous casting machine; and the control instructions of all the function modules of the continuous casting machine are transmitted to the PLC modules of the corresponding function modules of the continuous casting machine through the OPC server so as to control continuous casting machine equipment to operate. According to the invention, the adaptation problem of the existing intelligent management algorithm and the complex process and variable working conditions of the continuous casting machine and the real-time problem of a data acquisition and transmission system can be effectively solved.

The invention provides a multi-ecology user dynamic growth level management method and device based on pan-entertainment, equipment and a storage medium, user behavior data is asynchronously collected through a message queue, a user behavior feature vector containing multiple behavior type feature values is constructed, and a multi-ecology user dynamic growth level management algorithm is established based on the feature vector. User points are calculated through weighted operation of configuration weights and dynamic adjustment coefficients, historical points and monthly points are combined through the weight coefficients to obtain a comprehensive score, and balance evaluation of long-term value and short-term activeness of users is achieved. Determining a user grade through a grade mapping function according to the comprehensive score, dynamically adjusting a grade state based on upgrading and grade preservation conditions, and updating a dynamic adjustment coefficient in real time according to user grade change and contribution degrees of various behavior types to form a self-adaptive grade management closed loop; and the system can automatically learn and optimize the importance degrees of different behavior types, so that a real fair and intelligent user value evaluation system is realized.

The invention provides an intelligent terminal management method and system and a readable storage medium. The method comprises the steps of obtaining an application program started by a user in a current intelligent terminal; determining a target application program; obtaining the remaining duration of the task being executed from the target application program; obtaining the current residual electric quantity of the intelligent terminal at the current time; predicting a first endurance duration of the current intelligent terminal in the first operation environment through an electric quantity endurance prediction model; predicting a second endurance duration of the current intelligent terminal in a second operation environment through an electric quantity endurance prediction model; and when the residual duration is greater than the first endurance duration and less than the second endurance duration, determining an application program exit scheme through a preset management algorithm, so that the currently executed task of the target application program can be completed. According to the method, intelligent management is performed on the application program to ensure that the currently executed task of the target application program is smoothly completed, and the experience feeling of a user on the intelligent terminal is improved.

A ship lock automatic control system and method based on parallel theory, the system comprises a parallel ship lock operation management and control integrated platform, a ship lock operation process parallel control model, a ship lock operation process parallel control algorithm module, a ship lock passing process parallel control model, a ship lock passing process parallel management algorithm module, a time-based ship lock parallel management and control database, a ship lock equipment state monitoring module, a ship lock passing plan monitoring module, a passing ship state monitoring module, and a lock chamber water level monitoring module. The purpose of the present application is to solve the technical problems of high risk of ship lock operation and passing safety and low efficiency, which are caused by the fact that the existing ship lock operation and passing are analyzed by manually combining video monitoring information, voice interaction information and PLC information to obtain corresponding decisions and output instructions.

The invention discloses a large model operation method and device based on edge equipment, equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a to-be-operated large model, and carrying out the optimization of the to-be-operated large model after preprocessing based on the hardware characteristics of the edge equipment; determining the task priority of a to-be-executed task corresponding to the optimized model based on the resource condition of the current edge device; allocating the to-be-executed task to a pre-established model collaborative operation framework according to the task priority, and analyzing the to-be-executed task in the allocation process, so as to deploy the to-be-executed task to a load balancing node of the model collaborative operation framework according to an analysis result; and managing the related parameter data by using a preset data cache management algorithm to pre-load to-be-used data in the related parameter data into the edge device, so that the optimized model executes a corresponding to-be-executed task based on the to-be-used data through a load balancing node of the model collaborative operation framework.

This invention provides an energy management method for hybrid vehicles. First, traffic condition information and vehicle status information are simultaneously acquired and a database is generated. Then, the acquired information is used as the state space, and the reference SOC trajectory is used as the action space. Combined with a lower-level energy management algorithm, the upper-level deep reinforcement learning agent is trained until convergence. Finally, the neural network of the trained deep reinforcement learning agent is extracted as the optimal reference model for battery SOC. Based on the neural network model and combined with the lower-level energy management algorithm, the energy consumption of the entire vehicle is allocated. This invention not only solves the problem of the difficulty in determining the SOC trajectory in energy management strategies, but also improves the effectiveness, generalization, and stability of energy management strategies for new energy vehicles under actual road conditions, thus possessing many beneficial effects not found in existing technologies.

The application provides a one-to-one code marketing fund safety management method, and particularly relates to the field of marketing fund management algorithm. The application binds the fund flow identity and the state node in the block chain account book by generating a unique dynamic two-dimensional code and a master key index for each commodity, uses zero-knowledge proof to ensure that the fund data is credible and privacy-protected, and realizes automatic execution of the on-chain smart contract of fund transfer. Further, a graph neural network is introduced in combination with a time series model to construct a dynamic evolution fund path atlas for the fund transfer process, accurately identify abnormal behaviors of fund path deviating from the regular mode, effectively prevent fund reflux and abnormal aggregation, and improve the automatic detection and real-time response capability of fund safety. The application significantly enhances the safety, transparency and intelligent level of marketing fund management, realizes credible circulation of marketing funds and efficient early warning of abnormal behaviors.

The application relates to the field of retail digitization management and asset supervision, and discloses a store goods display taking and placing management algorithm based on passive RFID technology, which comprises the following steps: acquiring radio frequency characteristic flow of a target asset and a neighborhood reference label; extracting neighborhood group feature distribution and mapping a suppression operator to offset field environment noise; stripping common mode disturbance in a phase evolution sequence according to the suppression operator to extract a single body space offset; and mapping the offset to a business state machine to determine asset interaction confidence. The application realizes deep decoupling of radio frequency physical fluctuation and commercial semantic state, filters out transient physical noise through a neighborhood beacon interference suppression mechanism, ensures data consistency in asset display and transfer migration, and improves asset mapping precision of a management system without adding sensing hardware.

The invention relates to the field of nuclear engineering equipment health management, in particular to a dynamic binding method of an equipment health management intelligent algorithm and a related product, and the method comprises the steps: configuring an algorithm library and a fault library; setting an algorithm binding relation; in the algorithm operation environment, according to the algorithm binding relation, measuring point data of the equipment to be analyzed are obtained, the measuring point data serve as input of an algorithm, and the algorithm is executed for reasoning calculation; outputting an equipment health state diagnosis or prediction result bound with the fault mode; through standardized management, dynamic binding and automatic operation of the intelligent algorithm, support is provided for rapid deployment and operation of the intelligent health management algorithm on a platform and efficient use of the algorithm, the burden of operation and maintenance personnel of the intelligent algorithm is relieved, and convenience is also provided for rapid iteration of the intelligent health management algorithm.

The invention discloses hemodialysis water treatment equipment with an active protection function and a control method of the hemodialysis water treatment equipment. The hemodialysis water treatment equipment comprises an RO high-pressure pump motor, an intelligent variable-frequency driver, a temperature sensing module and a controller, the RO high-pressure pump motor is used for driving the reverse osmosis membrane assembly; the intelligent variable-frequency driver is used for controlling the operation of the RO high-pressure pump motor and receiving an external control instruction; the temperature sensing module is used for collecting the temperature of the RO high-pressure pump motor; a power consumption wall management algorithm and an improved CLFormer model are configured in the controller; constructing a dynamic thermal model through a power consumption wall management algorithm, and calculating a power upper limit value; and an improved CLFormer model introduces a thermal phase guidance differential fusion mechanism to generate a thermal risk prediction value, and when an overheating trend exists, a power limit instruction is generated, so that the operation power of the motor is limited below a power upper limit value. According to the method, the dynamic thermal model and the improved CLFormer model are fused, and active power limiting protection of hemodialysis water supply is achieved.

The invention provides a safety management and control system and method for a marketing field operation platform, and relates to the technical field of power marketing operation safety management, and the system comprises a data processing module which is used for obtaining operation plan data, work order data, field operation data and environment data; the security management and control module is in communication connection with the data processing module and is used for executing a security management and control algorithm model; and the risk early warning and processing module is in communication connection with the safety management and control module and is used for generating early warning information or executing a process control instruction according to an algorithm output result. Through the key job consistency detection unit, text semantics and key fields of plans and work orders are automatically quantified and compared, and a judgment threshold value is dynamically set, so that out-of-range jobs are effectively eradicated, automatic blocking of inconsistency is realized, and the problem that manual checking of the content consistency of the plans and the work orders is unreliable is solved.