28results about How to "Improve dynamic tuning performance" patented technology

The invention discloses a reservoir group scheduling interval multi-target optimization method under an uncertain condition, and belongs to the technical field of reservoir optimization scheduling. The method comprises the following steps: firstly, establishing an innovative cascade reservoir group interval multi-target scheduling model; secondly, providing a double-population dynamic coordination interval optimization method for solving the interval multi-target scheduling model, and further obtaining an optimal scheduling scheme of the reservoir group; and finally, outputting an optimal scheduling scheme set of the reservoir group. According to the optimization method, through organic combination of a chaos-order mapping initialization strategy, a dynamic adaptive mutual promotion updating strategy and an elite guidance optimization strategy, optimization is rapidly and efficiently carried out to obtain a group of reliable and accurate scheduling scheme sets considering runoff uncertainty; an effective decision-making technical means for solving the cascade reservoir group optimization multi-target complex engineering problem is provided for a scheduling decision maker, the intelligent level and comprehensive benefits of water resource management are improved, and the capacity of a water resource system for coping with complex environments and uncertain factors is further enhanced.

The invention discloses an intelligent self-adaptive real-time task scheduling method and system based on multi-dimensional optimization. The method comprises the following steps: S1, inputting a task; s2, a DAG task is decomposed into independent sequential sub-tasks; s3, dynamically calculating the priorities of the tasks by adopting a multi-factor dynamic priority scheduling module, and updating the priorities of the tasks; s4, dynamically adjusting an acceleration factor by adopting a self-adaptive acceleration factor management module; s5, vertex correlation analysis is carried out, and a variance of processor load imbalance is calculated by adopting a load balanced distribution algorithm and is minimized; s6, in combination with static analysis and dynamic inspection, a hybrid schedulability judgment module is adopted to judge the tasks, and judgment results are fused; and S7, fusing decisions by adopting a decision fusion algorithm, obtaining a scheduling strategy through a scheduling strategy coordinator, executing the task, and monitoring the task in real time. Real-time monitoring and real-time optimization scheduling are realized, and the utilization rate of resources is improved.

The invention relates to the field of meteorological temperature measurement, in particular to a meteorological temperature measurement method and system based on an optical fiber sensor, and the method comprises the steps: collecting data information in an environment through the optical fiber sensor, carrying out the preprocessing of the obtained different parameter information, and providing a data basis for the meteorological temperature measurement method; establishing a meteorological temperature prediction neural network model according to the preprocessed data information, and predicting the meteorological temperature; the meteorological temperature measurement process is improved according to the requirements of different meteorological environments and the prediction result of the meteorological temperature; and evaluating the improvement result of the specific process of meteorological temperature measurement, establishing a temperature measurement evaluation model, and evaluating the effect of the temperature measurement result in practical application. High-precision temperature measurement is provided, meteorological temperature data can be monitored in real time through manual intervention, the change condition of the meteorological temperature is reflected in time, and the whole measurement process has high reliability and stability.

The invention relates to the technical field of intelligent positioning, in particular to an intelligent positioning system and positioning method applied to a spraying robot, and the positioning system comprises a light field data acquisition module, a particle tracking calculation module, a sound wave precision distance measurement module and a dynamic verification execution module. According to the method, the operation environment of the spraying robot is sensed in an all-around mode through synthesis of a multi-sensing technology, the accurate position of the spraying head is updated through a strategy of capturing light field data in real time and accurately calculating particle dynamics, the spraying precision is ensured, the real-time response capacity to environment changes and the dynamic adjusting capacity of the spraying process can be greatly improved, and the spraying quality is improved. The material waste is reduced, the coating quality and the production efficiency are improved, sound wave precise distance measurement is added, the robustness and reliability of the system in a complex industrial environment are enhanced through sound wave and light field information fusion, precise tracking is combined with real-time position adjustment, and it is ensured that the spraying quality reaches the optimal quality every time.

The invention provides an unmanned ship positioning method and system for an automatic refueling robot, and relates to the technical field of data processing, and the method comprises the steps: obtaining the global position information, local position information and environment dynamic parameters of an unmanned ship, extracting static feature data and dynamic interference feature data, carrying out the self-adaptive correction of basic positioning data, and carrying out the self-adaptive correction of the basic positioning data; the method comprises the steps of generating ship motion trend prediction information, calculating a docking preparation path of the unmanned ship according to a preset geometric model of a target docking point, generating a real-time control instruction according to the docking preparation path, and collecting relative position information, water flow disturbance information and obstacle information of a refueling interface in real time when the unmanned ship reaches the target docking point. Parameters needing to conduct fine adjustment on the posture of the refueling mechanical arm are calculated, a refueling mechanical arm posture fine adjustment instruction is obtained, and the refueling mechanical arm posture fine adjustment instruction is used for adjusting the rotation angle, the horizontal position and the vertical height of the refueling mechanical arm; the intelligent degree and accuracy of refueling are improved.

The invention discloses a comprehensive lightning protection method and system for a large river model, and the method comprises the steps: S1, laying a conductive grid with a layered shielding characteristic at the periphery of the model, and shunting a lightning current to the ground through a multi-node grounding structure; s2, arranging electromagnetic field and electrostatic field detection equipment, and generating initial lightning activity analysis data; s3, calculating the gradient change of the electric field, the lightning discharge possibility and the path range through rule derivation and statistical analysis in combination with historical lightning data, and generating a lightning activity analysis result; s4, based on an analysis result, starting an intelligent early warning system, triggering an audible and visual alarm in a high-risk area, and recording a lightning activity range; s5, adjusting the shielding configuration of the conductive grid to enable the conductive grid to adapt to the dynamic change of lightning activity; and S6, after the thunder and lightning activity is finished, analyzing the monitoring data and generating a thunder and lightning event analysis report. According to the method, lightning monitoring, early warning and protection are integrated, and the lightning protection effect and the data traceability are improved.

The invention relates to the technical field of power system automation and intelligent control, and discloses a hydropower station multi-machine common tail water system grid-connected operation coordination optimization control method and system, and the method comprises the steps: building a hydropower station multi-machine common tail water surge chamber and tail water tunnel grid-connected operation regulation system mathematical model; adopting a Hopf bifurcation theory to solve a stability domain of control parameters of each unit speed regulator of the system; establishing a multi-objective optimization function, and selecting a disturbance load proportion of each unit and a speed regulator control parameter as optimized decision variables; the decision variables are optimized through MOPSO; all the control schemes are evaluated and analyzed by using a fuzzy satisfaction evaluation method, and the scheme with the highest standardized satisfaction is selected; and verifying the effectiveness of the multi-target coordination control strategy through simulation comparative analysis. According to the method, coordinated distribution of the load among the units is considered, the dynamic regulation performance of the units, the surge chamber and the power grid frequency is integrally improved, and technical support is provided for safe and stable operation of the hydroelectric generating set and the power grid.

The application discloses a kind of six-phase permanent magnet motor deadbeat direct current control methods based on dynamic time planning: by establishing dimension reduction transformation matrix, the influence of open-circuit fault on mathematical model and voltage complex plane distribution is analyzed, further utilize fault mathematical model and dimension reduction transformation matrix, the harmonic plane current reference value under different fault types is deduced, and the general formula of deadbeat direct current control rate is constructed.On this basis, with dynamic adjustment time as optimization goal, form motor system transient process standard optimization problem.To fixed current increment, the magnetic flux complex plane is divided, according to the magnetic flux information and voltage information of each magnetic flux grid, the motion time of each forward path in dynamic programming is calculated, and time planning is carried out in backward level mode, and an optimal path with shortest time is searched out in reverse direction, which can significantly improve the dynamic performance of motor in different fault-tolerant modes, and has good algorithm execution efficiency.

The present application provides a natural language-based enterprise user template production tool and method, which relate to the field of information processing technology. The tool and method receive enterprise users' template generation demand information; analyze store template design requirements based on an NLP model to determine demand feature information; perform template registration on the demand feature information based on template registration recognition multi-channel; perform rendering optimization based on a store product image set and a predetermined product image background set; then, perform animation recommendation comparison on the enterprise users to generate user store templates; and perform correlation adjustment on the user store templates based on real-time store monitoring data, thereby solving the technical problems of poor market response immediacy of user templates, low design accuracy and slow response speed, and achieving the goal of improving the degree of automation and personalization accuracy of template generation, so that the template can reflect the latest status of store operations and market changes in real time, thereby improving efficiency while reducing market investment costs.

The application relates to the technical field of computers and discloses a wireless micro-current tactile feedback game control device interaction method and system, which comprises the following steps: constructing an interaction feature matrix of user operation data and game scene data; generating a wireless micro-current control signal of a game control device through the interaction feature matrix and determining a body surface stimulation partition of the game control device; setting a stimulation combination mode of the wireless micro-current control signal and the body surface stimulation partition according to a game scene type and user operation preferences; extracting a response delay parameter and a stimulation coverage index in the stimulation combination mode, calculating a stimulation deviation value of the wireless micro-current control signal; calculating a tactile feedback threshold value corresponding to the game control device by using the stimulation deviation value; and generating a micro-current tactile feedback scheme of the game control device by combining the stimulation combination mode and the tactile feedback threshold value. The application can significantly improve the game immersion of users.

The invention relates to the technical field of signal processing, and provides a composite signal control method and device for nerve stimulation, equipment and a storage medium. The composite signal control method for nerve stimulation comprises the following steps: outputting an initial composite signal to a target neuron; acquiring response signals of the target neurons in real time and extracting key features; and based on the key features, adjusting signal parameters of the initial composite signal to obtain a target composite signal and outputting the target composite signal. Response signals of target neurons are collected in real time, key features are extracted, initial composite signals are adjusted according to the key features, the response signals are continuously collected in the whole process essentially, signal parameters are adjusted, and the purpose of improving the dynamic adjustment capacity and optimization accuracy of the composite frequency modulation signals is achieved. Therefore, the nerve cell excitability is stimulated by using the composite frequency modulation signal.

The invention relates to the technical field of data transmission control, and discloses a Bluetooth headset connection control method and device, equipment and a storage medium. The method comprises the following steps: constructing an initial Bluetooth connection topology network of a target Bluetooth earphone and a plurality of local terminal devices; environment data are collected, and an initial connection decision list is created; carrying out a connection decision test on the target Bluetooth earphone and each local terminal device, and collecting the data rate and transmission power of each local terminal device; performing feature extraction and coding vector conversion to generate a connection test coding vector; performing connection quality analysis through the connection quality monitoring model to obtain a connection quality index; and performing network variable weight optimization and decision list optimization on the initial Bluetooth connection topology network according to the connection quality index, and generating a target connection decision list, thereby realizing intelligent connection selection between the Bluetooth earphone and the local terminal equipment, and further improving the data rate and transmission power of the Bluetooth earphone.

The invention discloses an unmanned aerial vehicle ad hoc network optimal same frequency point dynamic adjustment method, and relates to the technical field of wireless communication, and the method comprises the steps: S1, building a synchronous frequency point candidate library of ad hoc network nodes; s2, periodically acquiring background noise information of each synchronous frequency point of the ad hoc network node in the synchronous frequency point candidate library; s3, acquiring an optimal synchronous frequency point of the ad hoc network node in the current period according to the background noise information of the ad hoc network node; s4, judging whether the channel quality of the ad hoc network nodes in the current period is lower than a threshold value or not, if so, entering the next step, otherwise, returning to the step S2; and S5, switching the synchronous frequency point used by the current ad hoc network node to the optimal synchronous frequency point, and updating the synchronous frequency point candidate library in the step S1. According to the technical scheme provided by the invention, the synchronization frequency point used in the current period is dynamically adjusted according to the channel quality, and the problem that the synchronization frequency point is interfered and data is lost is solved.

The application discloses a kind of top coal crushing degree prediction methods based on image recognition, belong to image recognition field, including: real-time acquisition top coal image and analysis definition and edge sharpness, automatically adjust camera focus to obtain high-quality image, apply edge detection algorithm to extract coal block shape and size distribution characteristics, determine crushing degree parameter.If parameter matches with preset threshold value, then it is combined with geological strength and mining depth to predict crushing degree distribution by neural network, analyze change trend and judge whether to need to adjust mining process parameter.Optimized parameter is handled historical data by feedback learning mechanism, determines self-learning adjustment value and updates neural network model, to realize more accurate crushing degree prediction and mining process closed-loop control.The application is fused by image processing, feature extraction and neural network prediction, significantly improves top coal crushing degree identification precision and mining efficiency, and optimizes process parameter dynamic adjustment capability.

The application relates to the technical field of electric energy conversion control, and discloses a marine cascade architecture voltage balance logic scheduling system, which comprises a cascade power sub-module, a sampling unit and a power balance controller. The power balance controller is integrated with a transient state prediction compensator, which is used for calculating second-order difference parameters of a voltage sampling sequence, identifying a marine load energy pulsation trend and searching for a trigger time advance. The power balance controller is also used for performing phase offset on a voltage balance lag window, adjusting a switch bridge arm driving signal according to the trigger time advance. The application realizes alignment of a scheduling instruction execution time and a marine load pulsation period by guiding dynamic contraction of a lag window width through difference parameters, offsets a sampling circuit group time delay, reduces power device transient state electric field stress, suppresses sub-module voltage oscillation and delays a thermal aging process.

This invention discloses an intelligent scheduling system for path planning based on UAV inspection data acquisition, relating to the fields of UAV inspection and intelligent scheduling technology. It includes a unified organization module for inspection data acquisition, which performs time alignment, spatial mapping, and unified encoding processing on positioning data, attitude data, environmental perception data, inspection image data, task execution status data, and resource status data to generate a set of inspection status units. In this invention, the unified organization module performs time alignment, spatial mapping, field parsing, joint matching, and unified encoding processing on positioning data, attitude data, environmental perception data, inspection image data, task execution status data, and resource status data to generate inspection spatiotemporal status data and a set of inspection status units. This allows multi-source inspection data, which was originally scattered and inconsistent in expression, to form a continuously callable organizational result under a unified time and spatial location.

The invention discloses a solar array simulator and a method for improving its dynamic performance, which relates to the field of programmable power supply. In a simulation mode, a voltage control loop is shielded, an output terminal voltage feedback signal is sampled, and an IV curve current programming reference value is obtained by looking up a table with the output terminal voltage as an index, and the output of the IV curve is completed with a current control loop. In order to increase the output operating point switching speed, a differential feedback signal of the dynamic change of the output terminal voltage is added to the current control loop to improve the dynamic adjustment performance of the simulator, and a voltage clamping circuit is combined with an FPGA programming control method to limit the feedback amount of the dynamic change of the voltage, so as to ensure the loop stability and effectively improve the dynamic response performance of the simulator when switching between different operating points.

The invention belongs to the technical field of intelligent warehousing and sorting, and particularly relates to a scheduling control method and device, a computer readable storage medium and electronic equipment. The method comprises the following steps: acquiring environment state information and material order information; task lists are generated according to the environment state information and the material order information, and various task lists to be executed are obtained; the various types of task lists are disassembled, and each sub-task after being disassembled is obtained; and allocating each sub-task to each corresponding execution device, so that each execution device executes each sub-task. According to the method and the device, various task lists to be executed can be adaptively generated according to the environment state information and the material order information, and the task lists are disassembled into the sub-tasks to be distributed to the corresponding execution devices, so that the overall dynamic adjustment capability is effectively improved.

The present invention provides an intelligent ship heading control method and system based on variable domain fuzzy logic, which belongs to the field of intelligent control of ship motion. In view of the control difficulties of intelligent ships in complex navigation environments caused by model uncertainty, the present invention proposes a data-driven adaptive heading controller, and innovatively introduces the concept of "variable domain" to optimize the traditional fuzzy self-tuning PID control method. By designing an adaptive scaling factor to dynamically adjust the fuzzy domain of input variables and output variables, it not only overcomes the high dependence of traditional fuzzy PID control methods on rules, but also significantly reduces the computational complexity and enhances adaptability to dynamic environments. This method greatly improves the adaptive ability of ship heading control and ensures excellent control effects under variable navigation conditions.

The invention relates to the technical field of voltage regulation, and discloses a MOS field effect tube threshold voltage regulation method, device, equipment and storage medium, wherein the method comprises: scanning multiple groups of gate voltages and drain voltages of the MOS field effect tube based on initial structural parameters to obtain a multi-dimensional voltage-current characteristic data matrix; performing feature extraction and fitting to obtain an initial threshold voltage function; calculating an actual threshold voltage value and performing comparison to obtain a threshold voltage deviation; designing ion implantation parameters to perform structural parameter regulation to obtain the regulated structural parameters; performing multi-temperature point threshold voltage simulation to obtain a temperature-threshold voltage response curve; constructing an adaptive PID controller and performing dynamic compensation of the threshold voltage, and outputting a real-time threshold voltage optimization strategy, wherein the method can comprehensively consider multiple factors such as device structural parameters, process fluctuations, temperature influence, etc., to achieve accurate control and dynamic compensation of the threshold voltage.

The present application relates to the technical field of power systems, and discloses an energy storage system, a control method, an electronic device, a storage medium and a program product, the energy storage system comprising a plurality of energy storage modules, each energy storage module comprising: a communication unit for sharing operation state data among the plurality of energy storage modules; and the control unit is configured to acquire the operation state data of other energy storage modules through the communication unit, and dynamically elect two energy storage modules in the plurality of energy storage modules to form a cooperative host pair based on a multi-agent decision rule, and the cooperative host pair cooperatively adjusts the power grid voltage and the power grid frequency of the energy storage system. According to the invention, each energy storage module is configured with the control unit, and the communication unit is utilized to share the operation state data, so that the system can dynamically elect a collaborative host pair composed of two energy storage modules based on a multi-agent decision rule. And the problem that the reliability of the whole system is reduced due to the fault of the fixed host is effectively solved.

The invention relates to the technical field of network security, in particular to a network security monitoring system based on artificial intelligence, which comprises a data preprocessing module, an anomaly detection module, a fault mode learning module, a threshold dynamic adjustment module, an attack source positioning module, a behavior analysis and identification module, a decision support module and a recovery strategy optimization module. According to the method, the abnormal state can be efficiently identified through the isolation forest algorithm and the self-encoder model, the learning of the fault mode is deeper through the application of the long and short-term memory network, and the precise attack source positioning is realized through the combination of the self-regression differential moving average model and the graph database query technology; the accuracy of attack pattern recognition is improved by introducing the convolutional neural network and the graph neural network, the security decision is more scientific and reasonable by applying the analytic hierarchy process and the support vector machine algorithm, and the resource allocation and recovery strategy are optimized by using the genetic algorithm and the particle swarm optimization algorithm.

The application belongs to the technical field of double-core microbead preparation, and particularly relates to a double-core microbead production process based on a cone tip matching three-dimensional microfluidic chip and application. The production process comprises the following steps: (1) raw material conveying: conveying the required materials through different pipelines to the cone tip matching three-dimensional microfluidic chip under insulation conditions; (2) material flow shearing: shearing the required materials in the cone tip matching three-dimensional microfluidic chip to obtain double-core droplets; (3) cooling and forming; and (4) product collection. The cone tip matching three-dimensional microfluidic chip structure can be used for accurately producing double-core microbeads, can realize accurate wrapping of the double-core microbeads, can realize accurate regulation of the particle size of the double-core microbeads, and can provide double-core microbeads with high structural consistency and high yield. Meanwhile, the continuous production of the double-core microbeads can realize stable, rapid and large-scale preparation, so that the microbeads can be widely applied in the fields of medicine, cosmetics, food and the like.

The invention relates to an intelligent voice outbound method, which comprises the following steps that: owner information and a verbal skill template are collected and stored in a system database, and the owner information is encrypted information and at least comprises mobile phone number information and address information; importing owner information, and obtaining an owner information table to create an outbound task; converting the verbal skill template to obtain verbal skill voice streaming media; matching a seat according to the call-out task and calling a mobile phone number of an owner so as to dialogue the owner according to the verbal skill voice streaming media, thereby analyzing voice dialogue content of the owner and generating text dialogue content; and processing the text dialogue content, obtaining a text semantic analysis result, and selecting one execution strategy of continuous communication, hanging up and redialing to complete an outbound task. The invention further relates to an intelligent voice outbound device, electronic equipment and a storage medium. By using the intelligent voice outbound method and device, the electronic equipment and the storage medium provided by the invention, the problem that a voice outbound system is poor in efficiency, intelligence and reliability is solved.

The invention relates to a pipeline pressure test packet division method and system based on a three-dimensional model, and the method comprises the steps: constructing a pipeline construction three-dimensional model which comprises the attribute information of a pipeline; in a visual operation interface, receiving a labeling operation of a user on a pressure test packet range on the three-dimensional model, and calculating and displaying key parameters of the pressure test packet in real time based on attribute information of the three-dimensional model; the method comprises the following steps: matching pressure test packet parameters marked by a user with a pre-stored pressure test specification rule base, checking whether a pressure test packet conforms to a test specification or not, and marking parts which do not conform to the test specification; according to construction parameters set by a user, on the basis of a pipeline connection relation graph, equipment grouping is carried out, a pressure test packet division scheme is generated, integrity verification is carried out on the division scheme, and by introducing three-dimensional modeling and providing visual operation and intelligent verification, the technical problems that manual checking is large in workload, tedious in process and prone to making mistakes are solved.

The invention discloses an intelligent content tracking method based on a sharing link. The method comprises the following steps: S1, embedding a tracking code; s2, capturing user behaviors; s3, acquiring WeChat user information; s4, receiving and processing back-end data; s5, data storage; s6, data analysis; s7, carrying out data visualization; s8, exporting the report; in software development practice, pursuing of code conciseness, calling convenience and code redundancy reduction is a key step for improving code quality, enhancing maintainability, optimizing system performance and improving development experience, by simplifying parameter design, function or method calling can be more visual and efficient, and the development experience is improved. And the reusability of codes can be promoted, and potential error sources are reduced, so that a system architecture which is easy to understand and operates efficiently is constructed.

The invention discloses a reinforcement learning and Bayesian optimization-based student autonomous learning ability improvement method. The method comprises the following steps of S1, collecting a student behavior data set in a student learning process; s2, forming a learning feature set of student individuals; s3, establishing a learning path optimization model based on a hierarchical reinforcement learning algorithm; s4, key parameters in the high-layer reinforcement learning model and the low-layer reinforcement learning model are adjusted through Bayesian optimization; s5, a reward mechanism based on a reinforcement learning algorithm; s6, updating the learning behavior model of the student at the end of each learning cycle; and S7, forming a cross-stage task connection mechanism based on the long-term learning target of the high-level reinforcement learning model and the short-term learning task of the low-level reinforcement learning model, and automatically formulating a learning strategy after each learning stage for the student. According to the invention, the self-adaptability of the system and the learning efficiency of students are obviously improved.

The invention relates to the technical field of Internet, and discloses a certificate matching method, device and equipment, a storage medium and a program product, and the method comprises the steps: monitoring an access request initiated by a client; analyzing the access request, and determining a domain name parameter carried in the access request; obtaining a plurality of pre-configured certificates, and selecting a target certificate matched with the domain name parameter from the plurality of pre-configured certificates; and performing handshake connection with the client by using the target certificate. By implementing the technical scheme of the disclosure, a corresponding relationship between a domain name and a certificate does not need to be set on the load balancer, dynamic matching of the certificate based on the real-time access request is realized, complex security requirements are better adapted, the dynamic adjustment capability of the load balancer is improved, and the user experience is improved. And the processing efficiency and security of the load balancer on the high-concurrency requests are improved.